Positsioonid

Kandideerimine avaneb märtsis.

 

2024. aasta kevade kandideerimisvooru seni kinnitatud positsioonid

Kandideerimine avaneb märtsis 2024! 

Ettevõtte/asutuse üldinfo:

Reach-U, www.reach-u.com 

Areas of activity: data analysis platforms for telecommunications and media companies, optimization and profiling algorithms, data exploration user interfaces, geospatial data

Tutvustav/sissejuhatav lõik

Reach-U is working with customers around the world on unique data-driven projects, for example analyzing mobile networks, fusing data from mobile, internet and TV traffic. With our purpose-built technology our customers can perform business analysis much more interactively than with other tools.

 
Image
ReachU
Praktika korraldus:

Reach-U is located in Tartu, our working language is mix of English and Estonian. Hybrid work is common (remote individual + office teamwork).

Eelduslikud ülesanded praktikal

  • Build tools to assess the quality of customer datasets while maintaining privacy
  • Testing beta/new features of Google Maps, Mapbox, Deck.gl, applicability of WebGL in advanced visualization methods
  • Experimenting with new visualization methods of datasets in web browsers, usually d3j.
  • Designing, coding and evaluating the performance of algorithms to extract insights from real-life datasets
  • Desk study of publicly available prior art
  • Build tools for generating data processing/lineage diagrams (the code is mix of Python/Java/Spark/Airflow)

Eelduslikud uurimisteemad magistritööks

  • Identifying patterns in geographic and behavioural datasets
  • Detecting hotspots, changes or anomalies in spatio-temporal datasets
  • Interactive visualization methods of large datasets web in browsers
  • Various methods of improving location accuracy in mobile networks

(Tehnilised) ootused kandideerivale tudengile

  • Experience in Airflow/JavaScript/Java/Python/R
  • Preferably experience using Jupyter, Tableau, QlikView or similar
  • Familiar at least with the basics of statistical analysis and ML methods

(candidate does not need to have all of them, any abovementioned skill may be enough)

Ettevõttepoolne juhendaja

Elis Kõivumägi (Project manager, PhD student in the University of Tartu, Distributed Systems group)

Teet Jagomägi (Product owner, MSc in Geographical Information Systems)

… or someone else, depends on the profile of the candidate

Miks peaksid tahtma just meile tulema?

Reach-U is 30 years old Tartu University spin off. Initially we focused on geographic information systems, then mobile operators, today we serve the largest media company in North America.

We have several “mission impossible” projects currently under delivery, you can contribute with testing various new approaches. If they work well, the impact will be huge.

We mix back-end and front-end developers, data engineers, UX/UI design to create tools that serve people around the world.

We believe in teamwork. You will be full member of our team, but if you have a friend/partner you like to work with, we are happy to define a task where you can work as a mini-team.

Kandideerimistingimused

1) Please describe your experience in free form (perhaps link to portfolio/github, if you have any). 

2) Describe briefly (and even better, convincingly and attractively) your motivation, in which area you want to develop yourself.

3) when looking back at your hobby projects or courses at the university, would you be able to bring out some “wow!”, “heureka!” or “I like that!” moments? If yes, can you please describe?

 

Based on those three points above, we put together the short list of candidates we would like to meet. The goal is to test if we match. Maybe you have also 3 questions to us? 

 

Example of the task:

Method(s): Multidimensional clustering and interactive visualization 

Example dataset: TV viewership data that contains logs from set-top-boxes and website visits. 

Working hypothesis: in what household groups did the exposure to TV commercial increase visits to website (=generated lift)? 

 

  1. Clustering task: formulate automatically clusters of households who reacted to commercial more than others.

 

Data structure:

  1. household ID, true/false if household was exposed, true/false if household was exposed and visited website, true/false if household was not exposed, true/false if household was not exposed, but still visited
  2. household ID and list of household characteristics (e.g. lifestyle, home City etc.)

 

We can start with reasonably-sized dataset to build a demonstrator. The real dataset includes millions of households and hundreds of millions of view facts.

 

The formula of generating lift:

Image
lift

2) Optionally, make attractive interactive visualization of the clustering result. Some examples of visualization techniques, but do not take these as a firm guidance.

Image
ReachU

 

Image
ReachU

General info on company/organization:

AS SEB Pank, Home Page | SEB

Introductory paragraph

SEB is a leading Nordic bank with over 165 years of experience. SEB has a department for Customer Data and Strategic Transformations. In this department we use data to drive product innovation and support other division with data-driven solutions. Our team consists of experts in the field with a strong focus on advanced data analyses. We use data science methods and machine learning to create analytical insights and predictive models. Join our team to help us create the next generation of data-driven financial products.

Image/video

Career | SEB

Arrangement of collaboration:

  • Location
  • Format (physical presence vs working from a distance)
  • Language requirements (Estonian/English/either-or/both)

Possible to work in SEB Tartu Innovation Centre in Delta building or in Tallinn at SEB main office.

Knowledge of English is mandatory, knowledge of Estonian is a bonus. 

Expected general assignments

Main tasks during the project:

  • Development of data-driven products 
  • Analysis of corporate segment
  • Customer product use efficiency and data drive insights to improve it
  • Preparation of the data
  • Application of advanced analytics and machine learning to identify potential business opportunities
  • Creating models and insights

Expected topics for master’s thesis

The topic will be agreed upon with the student, considering the interests of both parties.

Possible directions:

  • Predictive analytics
  • Creating sales-oriented models
  • Data-driven business intelligence

(Technical) expectations for applying student

Expectations for the applicant:

  • Front-end and back-end development experience + Python skills
  • Experience with data warehousing, SQL and data processing
  • Basic experience with Git and Linux
  • Experience with advanced analytics
  • Will be able create visualizations of different graphs 

Supervisor designated by the partner

Kristel Kammer, Strategist at SEB Baltics

Kristina Lillo, Innovation Lead, leading collaboration between SEB and universities 

Why should you join us?

Join us to shape the future of banking with data-driven products. Serving 2 million customers in the Baltic, we prioritize sustainability, innovation, and customer-centricity. By joining our team, you'll contribute to pioneering solutions and redefine the banking experience, making a lasting impact in the industry.

Application process

The application process involves three steps:

  1. Applying with a CV and a motivation letter, where relevant experience and interests are explained. 
  2. Video interview with supervisors.
  3. Homework to assess the level of skills

General info on
company/organization:

Codemagic - CI/CD for mobile teams. DevOps. codemagic.io

Introductory paragraph

Releasing mobile applications is a nightmare and we’re tired of it!

Codemagic is designed for mobile so teams can set up their CI/CD pipelines to release mobile application to the stores.

Arrangement of collaboration:
● Location
● Format (physical
presence vs working
from a distance)
● Language
requirements
(Estonian/English/eith
er-or/both)

Collaboration:

Codemagic has a remote team working from different parts in EU, Africa, Middle East and Asia.

Format: Candidate can choose to work remotely or we have desks available at our co-working space at Mobi Lab - Akadeemia 3, Tartu.

Language: English

Expected general
assignments
Student shall become familiar with Codemagic product and it’s capabilities in order to help Codemagic users to learn.

For this particular project we propose that student will try to use language models to improve how new users can learn and adopt Codemagic product.

Project success is measured by adoption rate of the idea student will develop as well as product metrics that it should influence.
Expected topics for master’s
thesis
For example:
● Language models in DevOps for mobile developers.
(Technical) expectations for
applying student
For example:
● Interested in language models
● Interested in mobile application development
● Good understanding of CI/CD
● Can use Codemagic.io product
Why should you join us? Codemagic is a small team of 24 talented people. Our customers are some of the best mobile and devops teams in the world like Toyota, Google, SmartID.

We want to make our product more accessible to the next generation and I think you can help us! We have tried, but haven’t really focused or invested a lot into trying to use language models in our product.

This is your opportunity to experiment and have a real impact.
Application process

Why do you want to join Codemagic?

Have you tried to use Codemagic product before?

In the second round of interview I would expect students to come up with ideas how to use language models in Codemagic product and we can discuss them together.

Candidate with best idea receives an offer.

 

 

Bolt is the European super-app with over 100 million customers in over 45 countries and over 500 cities across Europe and Africa. We seek to make cities for people, not cars, by accelerating the transition from owned cars to shared mobility. We offer better alternatives for every use case, including ride-hailing, shared cars and scooters, and food and grocery delivery. 

Image
Bolt HQ

 

Website https://medium.com/bolt-labs
Business domain Mobility
Location Tartu
Languages required English
Expected assignments ● Implementation of proof of concept (PoC)
● Reading, presenting, and reproducing previously published research related to the problem.
● Clear and transparent documentation of results
Topics for master’s thesis

We have different directions depending on the candidate's background and interest:
1. Machine learning models for long-term effects estimation in AB tests.
2. Machine learning models to monitor metrics and data quality.
3. LLM applications for knowledge-specific tasks in AB test platforms.

Expectations for applicant

● Experience with Python and data related data science libraries (Numpy, Pandas)
● Familiarity with SQL and Jupyter Notebooks
● Knowledge/interest in experimentation and causal inference topics.

Questions for the Applicant

1. What drew you to the specific topic you are applying for?
2. How do you see your work in this program contribute to your broader career goals, and how do you plan to leverage this experience to grow and develop professionally?
3. Describe a machine learning project you've worked on that you are proud of. What was it about? What were the challenges you faced, and how did you overcome them?

Supervisor Carlos Bentes, Senior Data Scientist
Why Bolt?

We value people's potential over experience. We believe that talented and hard-working people grow quickly, so we give them opportunities that most other companies would not.

The experimentation platform is a cross-functional distributed team of data scientists and software engineers that work on exciting problems with an impact, helping Bolt transform urban transportation and make cities for people, not cars.
Find more about Bolt:
https://bolt.eu/en/careers/life-at-bolt
https://bolt.eu/en-ee/cities/solutions

Video

 

 

Company description Enefit / Eesti Energia is a company which operates in the Baltic Sea electricity and gas markets and in the international fuel market. We have the most diverse energy portfolio in the Baltic Sea region: we produce energy from oil shale, biomass, tire chips, municipal waste, wind, sun and water. We use oil shale to produce liquid fuels – shale oil and oil shale gasoline as well as electricity and heat.
Introduction

We have a dedicated team who promotes and leads the innovations, we name this team E-Lab. The team consists of highly skilled specialists in the field of software engineering, data science and cloud engineering. We test different solutions in cooperation with other units and external partners in the framework of short-term prototyping projects. Data Scientists participate in E-Lab as core team members, providing their expertise and knowledge on machine learning, data analysis and optimization.

Data scientists work on diverse themes: renewable electricity production forecast, consumption forecast, electricity price forecast, data analysis for electricity production, for electric vehicles, energy storage…

Arrangement of collaboration

There are offices in Tallinn and Tartu. Part of the team is in Tallinn, another part in Tartu. Physical presence is asked on Tuesdays (if no lesson at university), one week in Tallinn, the other in Tartu. Transport is paid by the company. Other days can be whether remote, whether at the office.

English is spoken

Expected assignment
  • Create features to make better predictions.
  • Deliver data analysis.
  • Share your code
  • Present your work.
  • Finally, integrate your model with developers.
Expected topic Probabilistic (quantile) forecasting of electricity prices
Expectations for applying student
  • Good at mathematics, especially probability
  • Deep learning
  • Presentation skills
  • Interest for energy industry
Supervisor Jean-Baptiste Scellier, data science team lead
Why you should join us
  • Interesting topics. You can apply your skills to an industry that matters: energy. Due to more & more renewable energy, electricity production is less known and requires AI to make the system stable.
  • Strong team with several data scientists, so we learn a lot from each other.
Application process

Questions:

  • What kind of model would you try for time-series forecasting. For example, predicting electricity prices of the next 12 hours.
  • Why would you be a good fit for this position?

For the second round of admission, there will be a work assignment, as well as an interview with the supervisor.

 

Introduction

Swedbank is one of the largest banks in our home markets in the Baltics and Sweden with more than 7.3 million private and 600 000 business customers. We offer a wide selection of financial services and work every day to support people, businesses, and society to grow by promoting a healthy and sustainable economy.

Business domain Financial services
Location, format and language
  • Tallinn & Tartu
  • Hybrid working, with regular physical presence encouraged
  • English

Expected internship assignments

Our data science team is based within the Anti-Financial Crime (AFC) function of the bank, developing high quality and dependable data science products. In our team you will:

  • Participate directly in one of our delivery teams delivering products for AFC or the wider bank
  • Experience the Scaled Agile Framework for Enterprise (SAFe) way of working
  • Collaborate closely with our stakeholders to learn about the domain and ensure the products we build together are relevant to the bank’s needs
  • Apply state-of-the-art AI methods to extract knowledge and identify solutions from vast quantities of data 
  • Contribute to developing, deploying and operationalizing data science products
Possible directions for master’s thesis
  • Develop advanced methodology for creating synthetic data representative of our customers’ behaviors
  • Apply federated learning to share model information in collaboration with AI Sweden and other organizations
  • Mine and collate information from external sources to better understand our customers and their needs, either through traditional AI methods or Generative AI
Expectations for applicant
  • Team player that lives the Swedbank values of Open, Simple and Caring
  • Strong and humble communicator
  • Knowledgeable about the application of statistical methods, AI and machine learning to complex data sets
  • Familiarity with Python and common development practices (e.g. PEP 8, version control; testing)
Supervisor designated by the partner

Simon Whelan, Head of Data Science and Analytics, AFC

Andreas Karlsson, Team Manager in Data Science, AFC

Why should you join us? Swedbank is over 200 years old and one of the largest banks in each of our home markets, including Estonia. Our customers trust us to handle their finances, but we also have an obligation to society to prevent bad actors abusing the financial system. Come and join the largest data science team in Swedbank and help us build the products that protect society and bring the promise of AI to the whole bank.
Application process

Questions to address in an application either in text or through video

  1. Why do you want to work at Swedbank?
  2. Who or what inspired you to work in data science?
  3. In two or three sentences describe your favourite data science project that you have been involved in, focussing on why the project was important and the tangible outcomes your work to that goal.
  4. What do you want to achieve and learn working with Swedbank during your industrial masters?

If we take your application further, we will have a series of virtual interviews to learn more about you and to test your data science skills.

 

 

 


Eelmiste positsioonide arhiiv:

2023. aasta (6.vastuvõtt)

SEB on üle 165 aastase kogemusega juhtiv Põhjamaa pank. SEB-l on kliendiandmete ning strateegilise muutuse osakond, milles kasutatakse andmeid, et tõsta tooteinnovatsiooni ning toetada teisi osakondi andmepõhiste lahendustega. Meie tiimi moodustavad valdkonna eksperdid ning meil on tugev tipptaseme andmeanalüüsi fookus. Me kasutame andmeteaduse meetodeid ning masinõpet loomaks analüütilist vaatepunkti ning ennetavaid mudeleid. Tule liitu meie tiimiga ning aita meil luua järgmise põlvkonna andmepõhiseid finantstooteid ja -teenuseid!

Andmeteaduse tudengid on väga teretulnud! Kandideerimine oli avatud 17. septembrini. Tudeng alustas oma positsioonil SEB-s 2023. aasta oktoobris.

 

Koduleht www.seb.ee
Ärivaldkond Andmeteadus
Keelenõuded

Inglise keele oskus kohustuslik, eesti keele valdamine soovituslik. 

Asukoht

Vastavalt võimalusele kas SEB innovatsioonikeskuses Tartus Delta ettevõtlusmajas või SEB peakontoris Tallinnas Tornimäel.

Eelduslikud ülesanded praktikal

  • Ärisektori analüüs.
  • Teenuste kasutamise tõhususe parendamine.
  • Andmete ettevalmistus ning analüüs.
  • Võimalike ärivõimaluste tuvastamine läbi analüütika ning masinõppe kasutuse.
  • Rakenduste jaoks mudelite loomine ning soovituste tegemine.
  • Äriüksustele tulemuste tõlgendamine ning kommunikeerimine.
  • Andmepõhiste toodete arendamine.

Võimalikud uurimissuunad magistritööks

  • Ennustav analüüs
  • Müügile orienteerunud mudelite loomine
  • Andmepõhine ärianalüüs
Juhendajad ettevõttest
  • Üllar Rannik, PhD, Helsinki Ülikool. Üllar Rannik on SEB andmeteadlane. Omab kogemust laias teoreetilise ning praktiliste analüütiliste probleemide valdkonnas, sh andmekaeve, masinõpe ning mudelite loome. 
  • Kristina Lillo, SEB Balti Innovatsioonijuht. Kristina on peamine SEB ning ülikoolide koostöö kontakt.

Ootused kandideerijale

  • Pythoni oskus.
  • Kogemus SQL-i, andmetöötluse ning -ladustamisega. 
  • Git ja Linuxi kogemus algaja astmel.
  • Kogemus kõrgema andmeanalüüsi ning masinõppe projektidega.
  • Andmeteaduse ning masinõppe entusiasm.

Praktika korraldus:

  • Asukoht
  • Formaat (füüsiline kohalolu vs distantsilt töötamise võimalus)
  • Keel (eesti/inglise/emb-kumb/mõlemad)

Reach-U is located in Tartu, our working language is mix of English and Estonian. Hybrid work is common (remote individual + office teamwork).

Eelduslikud ülesanded praktikal

  • Build tools to assess the quality of customer datasets while maintaining privacy
  • Testing beta/new features of Google Maps, Mapbox, Deck.gl, applicability of WebGL in advanced visualization methods
  • Experimenting with new visualization methods of datasets in web browsers, usually d3j.
  • Designing, coding and evaluating the performance of algorithms to extract insights from real-life datasets
  • Desk study of publicly available prior art
  • Build tools for generating data processing/lineage diagrams (the code is mix of Python/Java/Spark/Airflow)

Example of potential task attached

Eelduslikud uurimisteemad magistritööks

  • Identifying patterns in geographic and behavioural datasets
  • Detecting hotspots, changes or anomalies in spatio-temporal datasets
  • Interactive visualization methods of large datasets web in browsers
  • Various methods of improving location accuracy in mobile networks

(Tehnilised) ootused kandideerivale tudengile

  • Experience in Airflow/JavaScript/Java/Python/R
  • Preferably experience using Jupyter, Tableau, QlikView or similar
  • Familiar at least with the basics of statistical analysis and ML methods

(candidate does not need to have all of them, any abovementioned skill may be enough)

Ettevõttepoolne juhendaja

Elis Kõivumägi (Project manager, PhD student in the University of Tartu, Distributed Systems group)

Teet Jagomägi (Product owner, MSc in Geographical Information Systems)

… or someone else, depends on the profile of the candidate

Miks peaksid tahtma just meile tulema?

Reach-U is 30 years old Tartu University spin off. Initially we focused on geographic information systems, then mobile operators, today we serve the largest media company in North America.

We have several “mission impossible” projects currently under delivery, you can contribute with testing various new approaches. If they work well, the impact will be huge.

We mix back-end and front-end developers, data engineers, UX/UI design to create tools that serve people around the world.

We believe in teamwork. You will be full member of our team, but if you have a friend/partner you like to work with, we are happy to define a task where you can work as a mini-team.

Kandideerimistingimused

1) Please describe your experience in free form (perhaps link to portfolio/github, if you have any). 

2) Describe briefly (and even better, convincingly and attractively) your motivation, in which area you want to develop yourself.

3) when looking back at your hobby projects or courses at the university, would you be able to bring out some “wow!”, “heureka!” or “I like that!” moments? If yes, can you please describe?

Based on those three points above, we put together the short list of candidates we would like to meet. The goal is to test if we match. Maybe you have also 3 questions to us? 

 

Example of the task:

Method(s): Multidimensional clustering and interactive visualization 

Example dataset: TV viewership data that contains logs from set-top-boxes and website visits. 

Working hypothesis: in what household groups did the exposure to TV commercial increase visits to website (=generated lift)? 

  1. Clustering task: formulate automatically clusters of households who reacted to commercial more than others.

Data structure:

  1. household ID, true/false if household was exposed, true/false if household was exposed and visited website, true/false if household was not exposed, true/false if household was not exposed, but still visited
  2. household ID and list of household characteristics (e.g. lifestyle, home City etc.)

We can start with reasonably-sized dataset to build a demonstrator. The real dataset includes millions of households and hundreds of millions of view facts.

 

RAITWOOD toodab ja turustab põhjamaisest okaspuust ehitus- ja viimistluspuitu. Meie Tartumaa täisautomaatne tootmiskompleks on Euroopa üks moodsamaid ning sealt ekspordime oma toodangut enam kui 40 riiki Euroopas, Aasias, Austraalias ning Ameerikas.

Koduleht

www.raitwood.ee

Ärivaldkond

Puidutööstus

Asukoht

RAITWOODi puidutootmise ja -viimistlemise kompleks koos modernse kontorihoonega asub Tartu külje all, 20-minutilise bussisõidu kaugusel kesklinnast.

Meil on võimalik teha hübriidtööd, nii et palju saab ära teha distantsilt.

Keelenõuded

Ootame RAITWOODi eestikeelset üliõpilast

Eelduslikud ülesanded

RAITWOOD tootmine on suuremas osas digitaliseeritud ja erinevaid andmeid genereeritakse palju. Olemas on andmeait, kuid sinna jõuab praegu vaid väike osa kõikvõimalikest andmetest. Soov on kas olemasolevat andmeaita laiendada või juurutada uus andmeaida lahendus. Sellest tulenevalt tuleks üliõpilasel:

  • analüüsida, süstematiseerida, dokumenteerida olemasolevad andmed;
  • teostada eelanalüüs ja nõuete kirjeldus planeeritavale andmeaidale;
  • luua tehnilised prototüübid ning võimalusel osaleda juurutamise juures.

Võimalikud uurimissuunad magistritööks

Konkreetne magistritöö teema kujuneb välja juhendajate ja üliõpilase koostöö käigus. Näitena mõned potentsiaalsed uurimisteemad:

  • andmevool põhineva andmeaida (streaming data warehouse) juurutamise võimalikkus ja otstarbekus RAITWOOD tootmises;
  • andmete modelleerimise parimate praktikate võrdlus tööstusettevõtte andmeaidale tuginedes.

Ootused kandideerijale

  • Oled analüütilise loomuga ja ei karda nuputamist
  • Saad hakkama SQL-iga
  • Ei jää hätta, kui tuleb natuke programmeerida/skripte kirjutada
  • Aimad, mis on andmeait ja ETL (Extract-Transform-Load) protsessid

Programmi kestel saad tutvuda selliste töövahenditega nagu Tableau, Talend, Microsoft Dynamics, GlobalReader; andmebaasidest MS SQL, MySQL ja PostgreSQL.

Juhendajad ettevõttest

Rein Hansson, IT-juht

Henri Parisalu, ärianalüüsi spetsialist

Akadeemiline juhendaja

Kristo Raun, suurandmete nooremteadur

I kandideerimisvooru küsimused

  1. Mis on Sinu kogemus erinevate andmebaaside ja analüüsidega? Palun kirjelda.
  2. Mis on Sinu suurimad saavutused tehnoloogia valdkonnas?
  3. Mis on Sinu kolme kuni viie aasta eesmärgid ja kus plaanite pärast IT-tööstusmagistrantuuri lõpetamist jätkata?
  4. Miks kandideerid RAITWOOD positsioonile?

II kandideerimisvoorus toimuv

Tahame, et sa:

  • tuleksid meiega vestlema;
  • teeksid sobivustesti.

RAITWOOD on oma valdkonnas üks maailma juhtivaid ettevõtteid, kus on:

  • arendav, koostööle häälestunud, toetav ja sõbralik tööõhkkond;
  • kaasaegne ja hubane kontor;
  • entusiastliku, õppimisele ja lahenduste leidmisele häälestunud hoiakuga kultuur;
  • meeskonnal sisemine tahe olla oma teemas pädev, oma ala proff;
  • väärtuseks tervislikkus ja tööheaolu.

Lisaks võid kindel olla, et meiega liitudes saad anda oma panuse parema keskkonnaga tuleviku loomisse! 

 

Bolt is the European super-app that has over 100 million customers in over 45 countries and over 500 cities across Europe and Africa. We seek to make cities for people, not cars, by accelerating the transition from owned cars to shared mobility, offering better alternatives for every use case, including ride-hailing, shared cars and scooters, and food and grocery delivery

Video: https://www.youtube.com/watch?v=1EQIXjvXKjM 

 

Website

https://medium.com/bolt-labs 

Business domain

Mobility

Location

Tallinn, Tartu (hybrid)

Languages required

English

Expected internship assignments

  • Participating in an iterative research process.
  • Formulating research questions.
  • Reading, presenting and reproducing previously published research related to the problem.
  • Creating, evaluating and documenting machine learning modelling approaches for improvement of text classification and semantic understanding tasks.
  • Maintaining reproducible research code.

Possible directions for master's thesis

1) Multilingual text classification

2) Semantic text classification

Expectations for applicant

  • Good analytical thinking
  • Experience in Python programming, including libraries such as Pandas and PyTorch. 
  • Understanding of machine learning (ML) modelling approaches with focus on NLP; ML model evaluation.
  • Familiarity with modern NLP models, methods and packages: LLMs, transformers
  • Proactive mindset, willingness to take initiative and getting things done.

Questions for the Applicant

1. What drew you to the specific topic you are applying for?

2. How do you see your work in this program contribute to your broader career goals, and how do you plan to leverage this experience to grow and develop professionally?

3. Can you describe a time when you worked collaboratively with a team to achieve a goal? What did you learn from the experience?

4. Describe a machine learning project you've worked on in the past. What were the challenges you faced, and how did you overcome them?

Supervisors

Maksim Butsenko, Staff Data Scientist, PhD

Why Bolt? 

We focus on potential not experience. We believe that talented and hard-working people grow quickly, so we give them opportunities most other companies would not.

 

Bolt is solving complex problems. It’s a value, especially for engineers who want to work on hard problems others have not solved before.

 

We have unique positions and projects. We're still growing as a company, so our positions and structure are not set in stone. We have a broad range of products across different continents. That means great opportunities for development and interesting problems to solve. 

Bolt is the European super-app that has over 100 million customers in over 45 countries and over 500 cities across Europe and Africa. We seek to make cities for people, not cars, by accelerating the transition from owned cars to shared mobility, offering better alternatives for every use case, including ride-hailing, shared cars and scooters, and food and grocery delivery

 

Website

https://medium.com/bolt-labs

Business domain

Mobility

Location

Tallinn, Tartu (hybrid)

Languages required

English

Expected internship assignments

  • Participating in an iterative research process.
  • Reading and presenting previously published related research.
  • Creating, evaluating and documenting reinforcement learning approaches for dispatching optimization.
  • Creation of reproducible research code

Possible directions for master's thesis

Reinforcement learning for dispatching optimization

Expectations for applicant

Experience with Python. Some familiarity with at least one deep learning framework (tensorflow, pytorch). Interest in optimization and reinforcement learning.

Questions for the Applicant

1. What drew you to the specific topic you are applying for?

2. How do you see your work in this program contribute to your broader career goals, and how do you plan to leverage this experience to grow and develop professionally?

3. Can you describe a time when you worked collaboratively with a team to achieve a goal? What did you learn from the experience?

4. Describe a machine learning project you've worked on in the past. What were the challenges you faced, and how did you overcome them?

Supervisors

Anatolii Prokhorchuk, Staff Data Scientist, PhD

Why Bolt? 

We focus on potential not experience. We believe that talented and hard-working people grow quickly, so we give them opportunities most other companies would not.

 

Bolt is solving complex problems. It’s a value, especially for engineers who want to work on hard problems others have not solved before. 

 

We have unique positions and projects. We're still growing as a company, so our positions and structure are not set in stone. We have a broad range of products across different continents. That means great opportunities for development and interesting problems to solve. 

Bolt is the European super-app that has over 100 million customers in over 45 countries and over 500 cities across Europe and Africa. We seek to make cities for people, not cars, by accelerating the transition from owned cars to shared mobility, offering better alternatives for every use case, including ride-hailing, shared cars and scooters, and food and grocery delivery.

Website

https://medium.com/bolt-labs

Business domain

Mobility

Location

Tartu, Tallinn (hybrid)

Languages required

English

Expected internship assignments

  • Participating in an iterative research process.
  • Reading, presenting and reproducing previously published related research.
  • Creating, evaluating and documenting machine learning modelling approaches for traffic modelling.
  • Maintaining reproducible research code.

Possible directions for master's thesis

Topics related to traffic modelling. E.g. an example topic could be: using machine learning approaches for traffic modelling using GPS probe data.

Expectations for applicant

  • Good analytical thinking.
  • An interest in traffic modelling.
  • Experience in Python programming, including libraries such as Pandas, sklearn, NumPy, (PyTorch/Tensorflow).
  • Understanding of machine learning (ML) modelling approaches; ML algorithm classes such as boosting, neural networks; ML model evaluation.
  • Proactive mindset, willingness to take initiative and getting things done.

Questions for the Applicant

  1. What drew you to the specific topic you are applying for?
  2. How do you see your work in this program contribute to your broader career goals, and how do you plan to leverage this experience to grow and develop professionally?
  3. Can you describe a time when you worked collaboratively with a team to achieve a goal? What did you learn from the experience?
  4. Describe a machine learning project you've worked on in the past. What were the challenges you faced, and how did you overcome them?

Supervisors

Joonas Puura, Machine Learning Engineer (Geo Data Science), MSc

Why Bolt? 

We focus on potential not experience. We believe that talented and hard-working people grow quickly, so we give them opportunities most other companies would not.

 

Bolt is solving complex problems. It’s a value, especially for engineers who want to work on hard problems others have not solved before. 

 

We have unique positions and projects. We're still growing as a company, so our positions and structure are not set in stone. We have a broad range of products across different continents. That means great opportunities for development and interesting problems to solve. 

Bolt is the European super-app that has over 100 million customers in over 45 countries and over 500 cities across Europe and Africa. We seek to make cities for people, not cars, by accelerating the transition from owned cars to shared mobility, offering better alternatives for every use case, including ride-hailing, shared cars and scooters, and food and grocery delivery.

Website

https://medium.com/bolt-labs

Business domain

Mobility

Location

Tartu, Tallinn (hybrid)

Languages required

English

Expected internship assignments

  • Collaborate on defining research questions and setting goals
  • Reading, presenting, and reproducing previously published research related to the problem.
  • Clear and transparent documentation of results
  • Implementation of proof of concept (PoC)

Possible directions for master's thesis

  1. Always valid p-values for continuous monitoring experiments
  2. Variance reduction using ML

Expectations for applicant

  • Experience with Python and data related libraries, like Pandas.
  • Familiarity with SQL
  • Knowledge/interest in experimentation and causal inference
  • Experience in ML modelling

Questions for the Applicant

1. What drew you to the specific topic you are applying for?

2. How do you see your work in this program contribute to your broader career goals, and how do you plan to leverage this experience to grow and develop professionally?

3. Can you describe a time when you worked collaboratively with a team to achieve a goal? What did you learn from the experience?

4. Describe a machine learning project you've worked on in the past. What were the challenges you faced, and how did you overcome them?

Supervisors

Carlos Bentes, Senior Data Scientist
Garret O'Connell, Senior Data Scientist, PhD

Why Bolt? 

We focus on potential not experience. We believe that talented and hard-working people grow quickly, so we give them opportunities most other companies would not.

 

Bolt is solving complex problems. It’s a value, especially for engineers who want to work on hard problems others have not solved before. 

 

We have unique positions and projects. We're still growing as a company, so our positions and structure are not set in stone. We have a broad range of products across different continents. That means great opportunities for development and interesting problems to solve. 

 Bolt is the European super-app that has over 100 million customers in over 45 countries and over 500 cities across Europe and Africa. We seek to make cities for people, not cars, by accelerating the transition from owned cars to shared mobility, offering better alternatives for every use case, including ride-hailing, shared cars and scooters, and food and grocery delivery.

 

Website

https://medium.com/bolt-labs

Business domain

Mobility

Location

Tartu, Tallinn (hybrid)

Languages required

English

Expected internship assignments

  • Participating in an iterative research process.
  • Formulating research questions.
  • Reading, presenting and reproducing previously published research related to the problem.
  • Creating, evaluating and documenting approaches for improvement of data platform offering.
  • Maintaining reproducible research code.

Possible directions for master's thesis

  1. Automation of solutions for data quality and performance issues
  2. Solving Data Governance with LLMs

Expectations for applicant

  • Experience with Python and data related libraries, like Pandas.
  • Experience with SQL
  • Knowledge/interest in data platforms and data governance
  • Proactive mindset, willingness to take initiative and getting things done.
  • Interest in LLMs

Questions for the Applicant

1. What drew you to the specific topic you are applying for?

2. How do you see your work in this program contribute to your broader career goals, and how do you plan to leverage this experience to grow and develop professionally?

3. Can you describe a time when you worked collaboratively with a team to achieve a goal? What did you learn from the experience?

4. Describe a machine learning project you've worked on in the past. What were the challenges you faced, and how did you overcome them?

Supervisors

Erik Heintare, Head of Analytics Platform

Pawel Kupidura, Senior Software Engineer

Why Bolt? 

We focus on potential not experience. We believe that talented and hard-working people grow quickly, so we give them opportunities most other companies would not.

 

Bolt is solving complex problems. It’s a value, especially for engineers who want to work on hard problems others have not solved before. 

 

We have unique positions and projects. We're still growing as a company, so our positions and structure are not set in stone. We have a broad range of products across different continents. That means great opportunities for development and interesting problems to solve. 

Swedbank is one of the largest banks in our home markets in the Baltics and Sweden with more than 7.3 million private and 600 000 business customers. We offer a wide selection of financial services and work every day to support the growth of people, businesses, and the society by promoting a healthy and sustainable economy.

Arrangement of collaboration:

  • Location
  • Format (physical presence vs working from a distance)
  • Language requirements (Estonian/English/either-or/both)

Location: Tartu & Tallinn

Format: Hybrid working, with regular physical presence encouraged.

Language: English

Expected internship assignments

Our data science team is based within the Anti-Financial Crime (AFC) function of the bank. You can:

  • participate directly in one of our delivery teams delivering products for AFC or the wider bank;
  • experience the Scaled Agile Framework for Enterprise (SAFe) way of working;
  • collaborate closely with our stakeholders to learn about the domain and ensure the products we build together are relevant to the bank;
  • apply state-of-the-art AI methods to extract knowledge and identify solutions from vast quantities of data;
  • contribute to developing, deploying and operationalizing data science products.

Expected topics for master’s thesis

  • Develop advanced methodology for creating synthetic data representative of our customers’ behaviors
  • Apply federated learning to share model information in collaboration with AI Sweden and other organizations
  • Mine and collate information from external sources to better understand our customers and their needs

(Technical) expectations for applying student

  • Team player that lives the Swedbank values of open, simple and caring
  • Good communication skills
  • Knowledgeable about the application of statistical methods, AI and machine learning to complex data sets
  • Familiarity with Python and common development practices (e.g., PEP 8, version control, testing)

Supervisor designated by the partner

Simon Whelan, Head of Data Science and Analytics

Juan Manuel Lorenzo Varela, Team Manager in Data Science

Why should you join us?

Swedbank is over 200 years old and one of the largest banks in each of our home markets, including Estonia. Our customers trust us to handle their finances, but we also have an obligation to society to prevent bad actors abusing the financial system. Come and join the largest data science team in Swedbank and help us build the products that protect society and bring the promise of AI to the whole bank. 

Application process

Questions to address in an application either in text or through video: 

  1. Why do you want to join Swedbank?
  2. Who or what inspired you to work in data science?
  3. In two or three sentences describe your favorite data science project that you have been involved in, focusing on the goal, why the project was important and the tangible outcomes.
  4. What do you want to achieve and learn working with Swedbank during the industrial master’s?

We will have a series of virtual interviews to learn more about you and to test your data science skills.

Eesti Energia is one of the largest Energy companies in Baltics. They operate in 6 markets: Estonia, Latvia, Lithuania, Poland, Finland and Sweden. In Estonia, EE operates under the name Eesti Energia, while brand name Enefit is used for international operations. 

Website: https://www.energia.ee

Business domain: Electricity production, distribution, sale of electricity, customer and consulting services

Working language: English

Position location: Eesti Energia’s R&D department in Tartu (Delta Business Building)

Energy industry is experiencing a paradigm shift that is visible through the following major developments:

  1. Switching to renewable energy sources - renewable energy sources are characterized by instability in production (wind and solar energy can only be produced when there is wind or solar).
  2. Energy storage systems - Energy storage (batteries) is one way to deal with fluctuations in renewable energy production.
  3. Distributed production - today, production is in the hands of a few large producers, but in the future we will see a large number of geographically distributed small producers.
  4. Electric cars - a completely new type of energy consumption, which also has integrated energy storage technology (battery).
  5. Smart devices - Many devices become remotely controlled, which means that the energy consumption of these devices can be changed (for example, we can temporarily reduce the electricity consumption of the heat pump when electricity is expensive).

But what is the most cost-effective energy solution for the specific customer? or How can we control the energy usage of those assets the most optimal way? Answering these questions will be the focus area of the Industrial Master’s student.

Website: https://www.energia.ee

Business domain: Electricity production, distribution, sale of electricity, customer and consulting services

Working language: English

Position location: Eesti Energia’s R&D department in Tartu (Delta Business Building)

Main tasks during the programme:

  • Developing various analytics and machine learning solutions to help achieve the balance, performance and optimality of the energy system of the future, i.e.:
    • forecasting energy production and consumption.
    • decide what is the most cost-effective way to move energy, e.g. should I store home-produced solar energy in a battery or consume it immediately?

Directions for thesis research area:

  • Time-series prediction, Supervised Machine Learning, Optimization.

The exact topic will be agreed in cooperation between the company and the student.

Why you should want to join us:

Help our customers on their journey to zero emissions and zero electricity cost. 

Supervisors: Kristjan Eljand

Necessary skillset for the applicant:

  • Data wrangling in Python.
  • Time-series prediction.
  • Supervised learning.

Conditions

  1. In the first round, we expect the students to solve the test task: https://docs.google.com/document/d/1XZ6YBKWUMn8jv3_ODCQtEh3ErRrZZyNROk7fhhHHB_E/edit?usp=sharing 
  2. In the second round, we’ll carry out the meeting with applicants.

2022. aasta (5. vastuvõtt)

RAITWOOD toodab ja turustab põhjamaisest okaspuust ehitus- ja viimistluspuitu. Meie Tartumaa täisautomaatne tootmiskompleks on Euroopa üks moodsamaid ning sealt ekspordime oma toodangut enam kui 40 riiki Euroopas, Aasias, Austraalias ning Ameerikas.


Koduleht www.raitwood.ee
Ärivaldkond Puidutööstus (hööveldatud puidu tootmine)
Asukoht

Praktika toimub RAITWOOD puidutootmise ja -viimistlemise kompleksis, mis asub Tartust 10 km kaugusel Reolas.

Reola ja Tartu vahet sõidab regulaarselt buss. Suuremas osas on võimalik praktiseerida ka distantsilt.

Keelenõuded Praktikale on oodatud eestikeelsed tudengid
Eelduslikud ülesanded praktikal

RAITWOOD tootmine on suuremas osas digitaliseeritud ja erinevaid andmeid genereeritakse palju. Olemas on andmeait, kuid sinna jõuab praegu vaid väike osa kõikvõimalikest andmetest. Soov on kas olemasolevat andmeaita laiendada või juurutada uus andmeaida lahendus. Sellest tulenevalt tuleks praktikandil:

  • analüüsida, süstematiseerida, dokumenteerida olemasolevad andmed;
  • teostada eelanalüüs ja nõuete kirjeldus planeeritavale andmeaidale;
  • luua tehnilised prototüübid ning võimalusel osaleda juurutamise.
Võimalikud uurimissuunad magistritööks

Konkreetne magistritöö teema kujuneb välja juhendajate ja praktikandi koostöö käigus. Näitena mõned potentsiaalsed uurimisteemad:

  • andmevool põhineva andmeaida (streaming data warehouse) juurutamise võimalikkus ja otstarbekus RAITWOOD tootmises;
  • andmete modelleerimise parimate praktikate võrdlus tööstusettevõtte andmeaidale tuginedes.
Ootused kandideerijale
  • Oled analüütilise loomuga ja ei karda nuputamist
  • Saad hakkama SQL-iga
  • Ei jää hätta, kui tuleb natuke programmeerida/skripte kirjutada
  • Aimad, mis on andmeait ja ETL (Extract-Transform-Load) protsessid

Teadmiseks, et praktika jooksul puutud kokku selliste töövahenditega nagu Tableau, Talend, Microsoft Dynamics, GlobalReader. Andmebaasidest MS SQL, MySQL ja PostgreSQL.

Juhendajad ettevõttest

Rein Hansson, IT-juht

Henri Parisalu, ärianalüüsi spetsialist

Akadeemiline juhendaja Kristo Raun, suurandmete nooremteadur

RAITWOOD on oma valdkonnas üks maailma juhtivaid ettevõtteid, kus on:

  • arendav, koostööle häälestunud, toetav ja sõbralik tööõhkkond;
  • kaasaegne, parimate seadmetega, ohutu töökeskkond;
  • entusiastliku, õppimisele ja lahenduste leidmisele häälestunud hoiakuga kultuur;
  • meeskonnal sisemine tahe olla oma teemas pädev, oma ala proff;
  • väärtuseks tervislikkus ja tööheaolu.

Lisaks võid kindel olla, et meil praktiseerides saad anda oma panuse parema keskkonnaga tuleviku loomisse!

We are more than sure - Pipedrive doesn’t need any introduction. In 2020 it became the fifth unicorn from Estonia.


Website www.pipedrive.com
Business domain Software development (CRM & revenue platform)
Location

Tartu

Our people work mostly in the office, as direct face-to-face communication is better for teamwork, but it is possible to do some work from the distance once you’re through on-boarding.

Language requirements Speaking English is a requirement
Expected internship assignments
  • Software planning, development and testing
  • Architectural research and design
  • Team-building
  • Cross-team communication
  • Presentation/demonstration of new solutions, ideas, research findings
Possible directions for master's thesis
  • Persistent messaging and data consistency between microservices
  • Applying machine learning / AI to different parts of our platform
  • Real-time data replication between multiple datacenters
  • Something user behavior & tracking - multiple topics are available
Expectations for applicant
  • Good communication skills
  • Some programming skills
  • Fun to work with :)
Supervisor

Marko Nõu, Head of Engineering

Marko will be your initial mentor, but each student will be assigned an individual supervisor during on-boarding.


Pipedrive is one of the pioneers that joined the program back in 2017 and has been participating ever since. We recognize the potential of what a master’s student can achieve and really appreciate the value of a good thesis. In total, there have been ten students that have joined us as part of the program – four of them are now employees and four are actively in the program.

Don’t be shy - apply for a position (and bring a friend as there are four positions open)!

Eesti Energia – internationally known as Enefit – is the largest energy company in Estonia. We operate across six markets: Estonia, Latvia, Lithuania, Poland, Finland and Sweden.


Website www.energia.ee
Business domain  Production, distribution and sale of electricity; customer and consulting services
Location

Tartu

You can work on location at our R&D department situated at the Delta building, or from distance.

Language Speaking English is required
Expected internship assignments

Developing various analytics and machine learning solutions that, for example, help us:

  • forecast production and consumption (How much solar energy will we produce in the next 5 hours? What will be the energy consumption of electric cars, given their historical data?);
  • decide what the most cost-effective way to distribute energy would be (Should we store home-produced solar energy in a battery or consume it immediately?).
Possible directions for master's thesis
  • Supervised machine learning
  • Optimization
  • Reinforcement learning
Expectations for applicant
  • Data wrangling in Python
  • Elementary know-how on supervised learning, optimizations and reinforcement-learning
Supervisors

Kristjan Eljand, Technology Scout

Peeter Piksarv, Data Scientist


The energy industry is experiencing a paradigm shift that is visible through the following major developments:

  • switching to renewable energy sources;
  • energy storage systems;
  • distributed production;
  • electric cars;
  • smart devices.

But what is the most cost-effective energy solution for the specific customer? And how can we control the energy usage of those assets in the most optimal way? Answering these questions will be the focus area of the Industrial Master’s student. By joining us, you will get an opportunity to gain lots of insight on how things are done in the energy industry and influence its future yourself!

Reach-U is working with customers around the world on unique data-driven projects, for example analyzing 5G networks, fusing data from mobile, internet and TV traffic. With our purpose-built technology our customers can perform business analysis much more interactively than with other tools.


Image
Visualization of geospatial data
Website www.reach-u.com
Business domain Software development (security, smart cities, telco)
Location

Tartu

Hybrid work (remote individual + office teamwork) is common at Reach-U.

Language requirements You can either be Estonian- or English-speaking
Expected internship assignments
  • Building tools to assess the quality of customer datasets while maintaining privacy
  • Testing beta/new features of Google Maps, Mapbox, Deck.gl
  • Experimenting with new visualization methods of datasets in web browsers, usually d3.js
  • Designing, coding and evaluating the performance of algorithms
  • Researching publicly available prior articles
  • Building tools for generating data processing/lineage diagrams (the code is mix of Python/Java/Spark/Airflow)
Possible directions for master's thesis
  • Identifying patterns in geographic and behavioral datasets
  • Detecting hotspots, changes or anomalies in spatio-temporal datasets
  • Interactive visualization methods of large datasets web in browsers
  • Various methods of improving location accuracy in mobile networks
Expectations for applicant
  • Experience in JavaScript/Java/Python/R
  • Preferably experience using Jupyter, Tableau, QlikView or similar
  • Familiar with the basics of statistical analysis and ML methods
Supervisors

Elis Kõivumägi, Project manager

Teet Jagomägi, Product owner


Reach-U is a Tartu University spin-off that is ~30 years old. Initially we focused on geographic information systems, then mobile operators. Today we serve the largest media company in North America. We have several “mission impossible” projects currently under delivery, to which you can contribute by testing various new approaches. If they work well, the impact will be huge.

We mix back-end and front-end developers, data engineers, UX/UI design to create tools that serve people around the world!

Estiko-Plastar loob innovaatilisi ja kliendikeskseid pakendilahendusi, lähtudes jätkusuutlikumast tootmisest. Arendame ja toodame pakendeid toidutööstustele – meie pakendis olevaid tooteid võid igapäevaselt kohata poeriiulitel.


Koduleht www.plastar.ee
Ärivaldkond Pakendilahenduste loomine ja tootmine
Asukoht

Tartu

Vastavalt olukorrale saab praktikaülesandeid täita ka distantsilt.

Keelenõuded Praktikale on oodatud eestikeelsed tudengid

Eelduslikud ülesanded praktikal / võimalikud uurimissuunad magistritööks

Estiko-Plastar on alustamas laiapõhjalist digitaliseerimist, eesmärgiga tõsta väärtusahela efektiivsust tervikuna, fokuseerides tootmisprotsessidele. Ettevõtte ambitsioon on luua tootmisprotsessi digitaalne kaksik, mis võimaldab paremini hinnata hetkeolukorda ja prognoosida uute tootmisvõtete mõju tulevikus. Selleks tuleb aga teha põhjalik eeltöö, mille saab suuresti jagada kahte etappi:

  • ettevõtte väärtusahela kaardistamine ja analüüs;
  • tootmisprotsesside kaardistamine ja analüüs.

Töö käigus õpib praktikant Estiko väärtusahelat ja tootmisprotsesse lähedalt tundma ja seeläbi avanevad võimalused mõjutada tehase tulevast käekäiku. Konkreetsed ülesanded ja uurimissuund magistritööks püstitatakse koos praktikandiga selliselt, et need oleksid kooskõlas tema ootuste ja oskustega.

Ootused kandideerijale
  • Omad baasteadmisi tarkvaraarendusest ja andmeteadusest
  • Omad baasteadmisi tootmisettevõtte väärtusahelast
  • Sul on analüütiline mõtlemine ja probleemide lahendamise oskus
  • Sul on soov näha ettevõtte tervikpilti ja sellega seotud mõõdikutest
  • Oled hea suhtleja ning oskad ennast selgelt väljendada
  • Julged meiega koos katsetada, eesmärgiga leida parimaid lahendusi

Konkreetsed tööriistad, millega praktikant tööle hakkab, lepitakse kokku vastavalt ootustele ja kogemusele. Kogemus ja/või valmisolek töötada mõnega järgnevaist tuleb kasuks: Apromore, Bizagi, Arina, ARIS, Rockwell Software Arena, Visual Components.

Juhendaja ettevõttest

Kerry Lumi, IT-juht

Akadeemiline juhendaja Eduard Ševtšenko, infosüsteemide kaasprofessor

Võimalus kaasa lüüa tehase arengus, panustades uute digitaliseerimis- ja automatiseerimislahenduste loomisesse. Saad hea ettekujutuse, kuidas juhtida tootmisettevõtte väärtusahelat, ja võimaluse rakendada oma probleemilahendamisoskused ettevõtte  lisandväärtuse tõstmiseks digitaliseerimise kaudu. Hea soorituse korral pakub ettevõte programmis osalejale lisatasu ja peale programmi lõpetamist avaneb võimalus jätkata ettevõttes tööd digitaliseerimise spetsialistina.

Telia on Eesti suurim telekommunikatsiooniettevõte. Otsime praktikanti andmete ja analüüsi valdkonnas. Analüüs on kriitiline komponent meie toimivuse ja edu tagamiseks. Andmepõhiste otsuste võimaldamine on meie peamine eesmärk.


Meie lugu

Koduleht www.telia.ee
Ärivaldkond Telekommunikatsioon
Asukoht

Tartu/Tallinn

Telia põhikontor asub Tallinnas – eeldame, et praktikant on valmis hinnanguliselt kord nädalas käima Tallinnas. Muul ajal on ka võimalus töötada distantsilt või kohapeal Tartus, kus meil on samuti väike kontor.

Keelenõuded Praktikant peab valdama nii eesti kui inglise keelt

Eelduslikud ülesanded praktikal

Praktika näeks sind osalemas meie analüüsiosakonna tegevustes, panustades nii ärianalüüsi kui ka andmeteadusega seotud tegevustesse. Praktika tulem avaldub nii meeskonnatöös kui ka individuaalses panuses.

Töö komponendid:

  • Analüüsiprotsesside kontroll/optimeerimine
  • Tiimijuhi abistamine
  • Iseseisvalt ärianalüüsi ja Tableau-aruande arendamine
  • Andmeteadusprojektides osalemine
  • Analüüsitöö dokumenteerimine
Võimalikud uurimissuunad magistritööks

Toome välja vaid mõned võimalikud magistritöö uurimisteemad. Tänu erinevatele ärivaldkondadele ja -protsessidele on uurimisteemade loetelu veelgi pikem.

  • Analüüsi protsess ja selle optimeerimine
  • Andmeteaduse võimalused moodsas ettevõttes
  • Andmeteaduse mudeli parandamine
  • Aruandmise ja arusaamise tasakaal – andmete ja informatsiooni roll
  • Visuaalne analüüs ja selle osised
  • Analüüsiprotsessi kaardistamine ja optimeerimine
  • Mahukam ärianalüüsi projekt
Ootused kandideerijale
  • Kasuks tuleb kogemus SQL-iga
  • Baasteadmised statistilisest analüüsist ja masinõppest
  • Kasuks tuleb projektijuhtimise kogemus
  • Proaktiivse kommunikatsiooniga
  • Hea tiimitöös
Juhendajad

Triin Tars, ärianalüüsi tiimijuht

Janika Aan, andmeteaduse tiimijuht

Kandideerimise kord

Kandideerimiseks on vajalik tutvustus (nt. CV kujul) ja motivatsioonikiri. Sealt edasi teeme videointervjuusid ning viimased valikud langetame, kui oleme ka näost näkku kohtunud. Enne lõplikku kokkulepet on võimalus kohtuda tiimiga ja töökeskkonnaga.


Andmed ja analüüs on kriitilise tähtsusega võimekus. Täna, muutuvas maailmas on õiged ja hea kvaliteediga otsused see, mis eristab võitjaid. 

Analüüsi väärtus on paljuski abstraktne. See eeldab, et tegevused ja eesmärgid on hästi kontrollitud ja väärtus, mida koos otsime on osapooltele selge. Meil osakonnas töötab üle 20 oma ala eksperdi, omades erinevaid kompetentse ja toetades lahendusi, mis mõjutab väga paljude inimeste elu.

Meie valdkond katab tegevusi andmearhitektuurist, aruandmisest, andmeteaduse ja IoT-lahenduste analüüsini ning palju muudki.

Tule meile appi!

2021. aasta (4. vastuvõtt)

We are more than sure - Pipedrive doesn’t need any introduction. In 2020 it became the fifth unicorn from Estonia.

Website: www.pipedrive.com
Business domain: CRM
Working language: English
Position location: Tartu

Main tasks during the programme:

  • Software planning, development and testing
  • Architectural research and design
  • Team building
  • Cross-team communication
  • Presentation / demonstration of new solutions, ideas, research findings

Directions for thesis research area:

  • Persistent messaging and data consistency between microservices
  • Applying machine learning / AI to search results and salesperson decisions
  • Real-time data replication between multiple datacenters
  • Something user behavior & tracking - multiple topics are available

Company's X-Factor:

Pipedrive is one of the pioneers that joined the Industrial Master's Programme in IT back in 2017 and has taken in five Industrial Master's students in total, so we really know the value of a master’s thesis. For example, Kiryl researched our software development process that gave us the needed assurement that we are on the right track. Alar, on the other hand, dug into the hackathons and gave us valuable insights that we didn’t have the opportunity to focus on otherwise. Don’t be shy - apply for a position (and bring a friend as there are six positions open)!

Supervisor: Marko Nõu, Head of Engineering

Expectations for the applicant:

  • Good communication skills, some programming skills, fun to work with. [/collapsed][collapsed class="collapsible-blue"]

Cleveron on südikas Viljandis asuv ettevõte, kellel on alati mõni üllatus varuks. Nagu aastal 2016, mil maailma suurim jaekett Walmart paigaldas Cleveroni pakirobotid USAs või kui aastal 2019 avati Viljandis Cleveroni akadeemia. Lahtise peaga, sooja südamega ning tugeva tööeetikaga tudeng – otsime just Sind! Liitu meiega ja ehitame koos tulevikku! 

Koduleht: https://cleveron.com/
Tudeng panustab: autonoomse tänaval sõitva robotkulleri arendusse
Töökeel: Eesti / Inglise
Positsiooni asukoht: Viljandi / Tallinn
(Viljandisse ja tagasi käib iga päev ka spetsiaalne buss Tartust)

Põhiülesanded programmi ajal

  • Panustamine projekti edasiarendusse, sh osalemine võimalikes lahenduste planeerimises, testimises ja järelduste tegemises
  • Masinõppimise põhjalik tundma õppimine, sh teadusartiklite läbitöötamine ning põnevate avastuste jagamine meeskonnaga
  • Meeskonnasuhtlus ja koostöö

Potentsiaalsed uurimussuunad:

Teemad, mis panustavad tervikliku sõidukite kaughaldus- ja kontrollsüsteemi loomisesse Cleveroni näitel, nagu näiteks:

  • Kaardilt huvipunktide tuvastamine
  • Objekti käitumise ennustamine
  • Videopildilt raja tuvastamine
  • Kõik, mis puudutab end-to-end masinõpet

Projekti X-faktor

Juhendaja: Martin Tammvee, Cleveron Mobility tarkvaraarendaja

Cleveronis puutud Sa kokku järgmiste tehnoloogiatega:

  • Uurimustöö tehniline keel omal vabal valikul – Python, Octave, Jupyter analoogid
  • Populaarsemad ML raamistikud – PyTorch, Tensorflow, Keras või analoogid
  • Produktsioonikeel on C++
  • ML suund on eelkõige Machine Vision

Have you ever wondered what it means to be a part of a startup? All the stories that surround the mysterious startup world… Are any of them true? Well, here’s your chance to find out, because Apromore offers you a deal - join the company via the Industrial Master’s Programme in IT! Apromore is a leading provider of open-source solutions for process mining and AI-driven business process improvement. Their flagship product is the result of award-winning research at The University of Melbourne and University of Tartu. In 2020 they attracted USD 4.77M in a Series A fundraising. Impressive, huh? That’s just the beginning! Don’t pass on the opportunity to study and be very hands-on in a startup - join Apromore today.

Domain: Business data analytics
Website: http://apromore.com
The student contributes to: the development of our high-fidelity business process simulation engine. This simulation engine will allow managers to measure the impact of any changes they plan to make to their business processes, before rolling out those changes.
Working language: English
Position’s location: Tartu (UniTartu Delta Centre)

Main tasks during the programme:

  • Contributing to the development of a microservice capable of using data extracted from enterprise software systems in order to generate high-fidelity simulation models to help managers make business improvement decisions. Work will include participation in the planning, development, testing and documentation.
  • Getting knowledge of robust microservice development and of libraries for process mining, machine learning and simulation, including conducting research and sharing findings with the Apromore development team in Estonia and Australia.

Potential directions for thesis research area:

  • Topics that contribute to the creation of a robust and scalable data-driven simulation engine for business process analysis, including:
  • Statistical learning techniques to derive simulation parameters from data
  • Machine learning optimization techniques to tune the simulation parameters
  • Use of scalable data analytics libraries 
  • Use of message queueing and streaming technology to build a scalable solution

Company’s X-factor:

  • We are a fearless and rapidly growing startup. In 2020, in the middle of the first Covid wave, we raised a 4M euros Series A investment round from a consortium of German and Australian investors. Later that year, we won a prestigious Bossie Award as one of the top-25 open-source software products for enterprises. We were also ranked as one of the top-101 Analytics startups worldwide according to the Startup Pill. We’ve grown from 5 to 25 people in 12 months and we're determined to grow up to the sky. We’re headquartered in Melbourne, Australia and with staff also located in Brisbane, Australia and in Tartu. We are global and digital native from birth and we deliver our process mining platform and consultancy services to companies worldwide.

Supervisor: Nikolay Roll, Product Analyst 

At Apromore, you’ll be working with the following technologies:

  • The technical language of the thesis is Python or Java.
  • Lots of technologies, including Docker, RabbitMQ, Impala/Parquet, etc.

Eesti Energia (EE) is an Estonian energy company founded in 1939. Traditionally, they have produced energy from the oil shale but the company is moving rapidly towards renewable energy sources. In 2020, almost 40% of the energy that EE produced came from renewable sources (compared to 16% in 2018). They operate in 6 markets: Estonia, Latvia, Lithuania, Poland, Finland and Sweden. In Estonia, EE operates under the name Eesti Energia, while brand name Enefit is used for international operations. If you join Eesti Energia, you will get an opportunity to gain lots of insight on how things are done in the energy industry and influence the future of it. 

Website: https://www.energia.ee
Business domain: Electricity production, distribution, sale of electricity, customer and consulting services
Working language: English
Position location: Eesti Energia’s R&D department in Tartu (Delta Business Building)

Main tasks during the programme:

  • Developing various analytics and machine learning solutions to help achieve the balance, performance and optimality of the energy system of the future, i.e.:
  • forecast production and consumption, e.g. how much solar energy will we produce in the next 5 hours; what will be the energy consumption of electric cars, taking into account their historical data.
  • decide what is the most cost-effective way to move energy, e.g. should I store home-produced solar energy in a battery or consume it immediately?

Directions for thesis research area:

  • Supervised Machine Learning, Optimization, Reinforcement learning

Project’s X-factor:
The energy industry is experiencing following major developments:

  1. Switching to renewable energy sources
  2. Energy storage systems
  3. Distributed production
  4. Electric cars
  5. Smart devices

Coordinating the production and consumption of these assets requires novel machine learning solutions. Eesti Energia is working actively towards building these solutions. This will also be the focus area of the Industrial Master’s student.

Supervisors: Kristjan Eljand and Peeter Piksarv

Necessary skillset for the applicant:

  • Data wrangling in Python
  • Supervised learning
  • Optimizations and Reinforcement-learning know-how.

Tööstusettevõte ei tähenda täna pelgalt tootmistehast. See tähendab ka suures koguses andmeid. Masinõppest huvitatud andmeteaduse tudeng, otsime Sind. Aitame Sul rakendada ülikooli teadmisi praktikas ja Sina näed enda töö vilju füüsilistel toodetel. 

Digitaliseerimislahendusi ning ärikonsultatsiooni pakkuv Columbus ja liimpuidutootja Barrus* panid seljad kokku tagamaks, et igast puitpalgist**, mis jõuab Barrusesse, sünniks maksimaalne väärtus ning midagi, sh ka saepuru, ei läheks raisku.

Koduleht: https://www.columbusglobal.com/et/ ; https://www.barrus.ee/
Äridomeen: Tööstusettevõtete andmed ja analüütika, liimpuidu tootmine
Töökeel: Eesti keel
Positsiooni asukoht: Columbuse Tallinna/Tartu kontor või MS Teams vahendusel. Ettevõte jätab tudengile vabad käed ise otsustada eelistatud formaadi osas.

Potentsiaalsed uurimussuunad:

  • Masinõppe/tehisintellekti rakendamine uurimistulemustele
  • Tööprotsesside analüüs optimeerimise eesmärgiga

Põhiülesanded programmi ajal:

  • Barruse  protsesside ja andmete kaardistamine
  • Eelnevate perioodide analüütika
  • Hüpoteeside seadmine, andmete märgistamine jms
  • Meeskondade vaheline suhtlemine
  • Tarkvara lahenduse proof-of-concept’i (koos)loomine ja selle põhjal magistritöö kirjutamine

Projekti X-faktor:
Võimalus kaasa lüüa kogu tarkvaraarenduse protsessi elutsüklis. Oled täisväärtuslik meeskonna liige kogu programmi vältel, saades mitmekülgset tuge ja õppimisvõimalusi kahe oma valdkonna tipptegija käe all. Saad võimaluse “käega katsuda”, kuidas üks tootmine käib ning peale programmi lõppu osapoolte soovil jätkama juba emba-kumba ettevõtte töötajana.

Juhendajad: Kristen Pugi (Columbus Eesti) ja Vaido Otsar (Barrus)

Ootused kandidaadile:

  • Omad baasteadmisi tarkvaraarendusest ja andmeteadusest
  • Sul on analüütiline mõtlemine ja probleemide lahendamise oskus
  • Oled hea suhtleja ning oskad ennast selgelt väljendada
  • Julged meiega koos katsetada ja analüüsida tulemusi

Varasem kogemus ei ole vajalik, kuid programmi ajal puutud Sa kokku järgmiste tarkvarade ja programmeerimiskeeltega:

*Barrus – elevant (Ladina k.)
**NB! Barrus väga hoolib Eesti metsast ning kasutab oma tootmises vaid sellist puitu, mis on varutud jätkusuutlikult majandatud metsadest. 

Reach-U is creating world-leading solutions for different industries like telco, security, smart cities and tourism. With more than 20 years of experience we have gathered skills in location based solutions, GIS and cartography. Our unique background delivers everything needed for launching solutions that include software, data, maps and support.

Website: https://www.reach-u.com/
Business domain: Data analysis technology for large datasets with special focus on location analytics
Working language: English and/or Estonian
Position location: Tartu

Main tasks during the programme:

  • Designing, coding and evaluating the performance of algorithms to extract insights from actual, real-life, datasets
  • Researching publicly available prior art

Directions for thesis research area:

  • Identifying patterns in geographic and behavioural datasets
  • Detecting hotspots and changes in spatio-temporal datasets
  • Interactive visualization methods of large datasets in browsers
  • Various methods of improving location accuracy in mobile networks

Company’s X-factor:

  • Reach-U is working with customers around the world on unique data-driven projects, for example analyzing 5G networks, fusing data from mobile, internet and TV traffic. With our purpose-built technology our customers can perform business analysis much more interactively than with other tools.

Supervisor: Elis Kõivumägi (Ph.D student in the University of Tartu, Distributed Systems group). Elis is involved in all cutting-edge projects with our customers, worked in the Demograft team for 7 years).

Expectations for the applicant:

  • Experience in JavaScript/Java/Python/R
  • Preferably experience using Jupyter, Tableau, QlikView or similar
  • Familiar at least with the basics of statistical analysis and ML methods [/collapsed][collapsed class="collapsible-blue"]

Singularity Creations is a small company that works on projects which get noticed and make a difference whether it is accounting, video marketing or video training. We have flexible hours, dedicated team and we strive to give our best in whatever we are working on – these little gray cells of Yours will get a lot of work. You will get a chance to build tools today that will redefine our tomorrow in the video industry. Jump on board!

Location: Tartu
Website: www.singularitycreations.ee
Business domain: Developing online services and information systems
Working language: English

Main tasks/opportunities during the programme:

  • Participate in building an asynchronous video training platform.
  • Take part in the entire development cycle.
  • Opportunity to lead or take the role of product owner.
  • Alternatively dive into both front- and backend coding and database design (JavaScript – NodeJS, GraphQL, Vue.js, MySQL, PostgeSQL).

Directions for thesis research area:

  • Possibilities of asynchronous video platforms.
  • Analyzing and optimizing sprint task estimation process.
  • Measuring and improving code delivery and quality via leveraging development and collaboration tools and/or processes.

Supervisor: Madis Kapsi (CTO) with his more than 10 years of coding experience he has vast knowledge in the field and he will be more than happy to teach You everything he knows.

Expectations for the applicant:

  • Great communication skills.
  • Familiar with software development tools and technologies (back-end/front-end development basics).
  • Team player who wants to contribute and learn, interests in possible leadership role.
  • Basic understanding of agile methods.

2020. aasta (3. vastuvõtt)

Websitewww.baltikagroup.com
Business domain: Fashion Design and Retail
Working language: Estonian. English is possible if needed.
Position location: Tallinn

Baltika Grupp has one position but two different profiles to choose from. 

PROFILE ONE

Main tasks during the programme:
Mapping of current IT as-is situation
Analysis of company data IT infrastructure and processes, with the focus on:
1. Order, Warehouse, Route Management, Inventory Management Systems upgrade vision and roadmap
2. Sales, CRM (omnichannel) to-be execution from IT perspective
    Architectural research
    Presentation / demonstration of new solutions, ideas, research findings
    Software planning and/or development, testing

Directions for thesis ressearch area:

  • Open for discussion, possible options:
  • Recommend IT architecture TO-BE vision and roadmap
  • Persistent messaging and data consistency between microservices
  • Applying machine learning / AI to search results and salesperson decisions

Company's X-Factor:
Baltika is already using a number of digital solutions, such as: 3D design for physical product creation and AI for inventory distribution across the Baltics. The following machine learning projects are already in process and we are planning to continue with them. Digitization also needs a change from the perspective of the entire data world and IT systems, so there are certainly challenges and experiences worth being part of!

Supervisor:
Kairi Rais, Head of Business Processes and IT

Expectations for the applicant:

  • Back-end development basics
  • Knowledges about modern technical environments (microservices, REST API, webservices, SaaS, message brokers etc)
  • Independent thinker, but at the same time team player
  • Willingness to learn new things
  • Practical understanding about Supply Chain

PROFILE TWO

Main tasks during the programme:

  • Data hygiene assessment
  • Assess the company state to be able to take advantage of and implement machine learning applications
  • Data exploration and analysis
  • Analysis of AI supporting subsystems (What data do company have? What data is missing? What data could company add to make data more valuable)
  • Leading development of projects (to be agreed)
  • Power BI dashboards set up (creating a data model and visuals)

Directions for thesis ressearch area:

  • Open for discussion, possible options:
  • Descriptions of data infrastructure with recommendations
  • Recommend easy to implement AI use-cases (low hanging fruit)
  • Defined roadmap for develope AI ideas
  • Recommended AI tools to implementation

Company's X-Factor:
Baltika is already using a number of digital solutions, such as: 3D design for physical product creation and AI for inventory distribution across the Baltics. The following machine learning projects are already in process and we are planning to continue with them. Digitization also needs a change from the perspective of the entire data world and IT systems, so there are certainly challenges and experiences worth being part of!

Supervisor:
Kairi Rais, Head of Business Processes and IT

Expectations for the applicant:

  • Back-end development basics
  • Knowledges about modern technical environments (microservices, REST API, webservices, SaaS, message brokers etc)
  • Independent thinker, but at the same time team player
  • Willingness to learn new things
  • Practical understanding about Supply Chain

Website:www.carrentalgateway.com/
Business domain: Car rental distribution platform
Working language: English, Estonian
Position location: Tartu

Main tasks during the programme:
You will be part of a self-organising team, who creates new web services and maintains the already existing ones. Our platform is built of small independent web services and the main programming languages we use are JavaScript (Node.js) and PHP. Our front ends are being developed in AngularJS and React.

Directions for thesis ressearch area:

  • Implementation of continuous delivery
  • Microservices in Go programming language
  • GraphQL optimal design and implementation

Company's X-Factor:
Car Rental Gateway is a platform for different Car Rental Distributors. We are an efficient, flexible, pragmatic, and fast-paced enterprise. We are putting great emphasis on data and are practicing data-driven decision-making. Car Rental Gateway aims to be a market leader in car rental distribution technology. Today our platform is being used by Expedia, who is one of the biggest players in the online travel sector. We have also developed software for Rentalcars.com, the biggest car rental broker on the market. Our aim is to continue growing, bring innovation and be the pioneer of technological solutions at the car rental distribution sector.

Supervisor:
Kaspar Soer, CTO

Expectations for the applicant:

  • Experience with different programming languages;
  • A good understanding of web services;
  • Experience with version management software (e.g., GIT)
  • Excellent English language skills

Websitehttps://lab.mobi
Business domain: Industry 4.0
Working language: English
Position location: Tartu

Main tasks during the programme:
The goal is to design and develop mobile apps which would help to improve the quality and effectiveness of the field workforce in various industries and warehouse workforce in factories. Delivering a system which is automated, integrated and easy to use will require a mix of the following skills as Database (SQL), Back-end (Java) and mobile (Android) front-end development with integration to 3rd party ERP systems and hardware as RFID readers, BT beacons, various sensors etc.

Directions for thesis ressearch area:

  • User experience for the mobile workforce
  • Mobility in manufacturing and logistics
  • Automated IT solutions for the mobile workforce
  • Data collection and data analyses for work optimisation

Company's X-Factor:
At Mobi Lab, we are UX and UI designers, software engineers and product managers who have common passion for customer experience in digital products.
We belive in:

  • Passion as the key driver in life
  • Diversity, flexibility and community
  • Independence and self-driven motivation
  • A hidden superstar in every person

Supervisor:
Allan Valm & Veiko Raime

Expectations for the applicant:

  • Skills in Java software development and SQL
  • High motivation to learn business processes and business analytics
  • Testing everything and writing automated tests for integrations
  • Independent, self-motivated and very responsive

Websitewww.overall.ee
Business domain: IT services, printing and imaging solutions
Working language: English and Estonian
Position location: Tartu

Main tasks during the programme:
Participation in specification and development of self-service printing environment components.
Those may include:

  • Mobile applications
  • Embedded device applications
  • Authentication technologies
  • Payment gateways
  • Reporting and usage data analysis including modelling and visualization
  • Dynamic discount system modelling
  • Usability testing

There is a possibility to get involved also with the predictive modelling work and ML activities for print fleet management.
This would entail:

  • Development of self learning predictive algorithms
  • Operational decision-making dashboard creation
  • Testing in live field service environment

Directions for thesis ressearch area:
Mobile application specification and development
Embedded application development for printing devices
Applying ML/AI possibilities to print fleet management and field service optimization

Company's X-Factor:
Overall Eesti is the leading provider of managed print services and solutions in Estonia. We develop and operate a unique public/private print service, Print In City. Print In City is currently available in Estonia, Latvia and Finland with pilots starting in the UK as well as selected countries outside of the EU. Overall is in the process of developing native methods and technology with the goal of transforming our print fleet management model to an efficient data driven and self learning predictive maintenance system to achieve significant cost and operational efficiencies. Overall provides equipment, solutions and services also in the areas of digital production print, multimedia presentation, professional camera and film. Our long time technology partners are global innovators Canon and HP.

Supervisor:
Your supervisor will be Overall’s systems architect and chief developer, Urmas Tamm. Urmas has a degree in Physics from the University of Tartu. For predictive fleet management work your supervisor will be Tõnis Haamer. Tõnis has an Informatics degree from Tallinn Technical University and is Overall Eesti board member.

Expectations for the applicant:

  • Experience in C# and ASP.Net
  • Knowledge of modern back-end and front-end development
  • Knowledge of mobile applications development
  • Experience and interest in Data Science Interest in learning and exploring new data modelling and visualization technologies and their application in business

Websitewww.pipedrive.com
Business domain: CRM
Working language: English
Position location: Tartu

Main tasks during the programme:

  • Software planning, development and testing
  • Architectural research
  • Team building
  • Cross-team communication
  • Presentation / demostration of new solutions, ideas, research findings

Directions for thesis ressearch area:
Persistant messageing and data consistancy between microservices
Applying machine learning / AI to search results and salesperson decisions
Real-time data replication between multiple datacenters
Something user behavior & tracking related - multiple topics there available

Company's X-Factor:
Pipedrive is one of the pioneers that joined the Industrail Master's Programme in IT back in 2017 and has taken in three Industrial Master's students in total, which means you will have students that have done the same path as you, as your colleagues.

Supervisor:
Marko Nõu, Engineering Manager

Expectations for the applicant:
Good communication skills, some programming skills, fun to work with.

Websitewww.postimeesgrupp.ee/
Business domain: Media
Working language: English/Estonian
Position location: Tallinn, Tartu (details will be agreed during the interview)

Main tasks during the programme:
We expect you to add value to our team with your webpages and application development experiences, among with knowledge thirst for frontend and backend technologies and languages
In addition, it would be beneficial if you'd have some knowledge in webpage/application optimization as well as modular and scalable software, API and object-oriented programming
In our day-to-day life we are using Node.js, Vue.js, PHP, Doctrine, Symfony, Laravel, MySQL, Docker, Python, but we are quite flexible and always trying to explore newest technologies and opportunities"

Directions for thesis ressearch area:
We would love you to do research and possibly your Master's thesis on a topic of using machine learning and natural language processing to discover and analyze patterns in articles, for expample:
Ability to identify and create keywords for articles using machine learning in the Estonian language even if the keyword itself has not been used in the article
Determine the tone of articles in the Estonian-language press through machine learning and compile statistics based on that"

Company's X-Factor:
Postimees Group is the Baltic region’s largest media group, the activities of which include print and online media content creation, television and radio production, e-commerce and classifieds portals, direct mail, publishing and printing services. Joing software development team, you will be working mostly on developing postimees.ee.
You will be able to choose the computer, OS and software that you feel the most comfortable working with.

Supervisor:
Alari Truuts, system architect

Expectations for the applicant:
Besides having (great) experience or deeper knowledge in the technologies that are mentioned above, you would be the perfect fit if you are curious team-player, who respects deadlines and is willing to go for that extra mile in order to achive goals.

Kodulehtwww.previser.fi
Äridomeen: Raamatupidamine
Töökeel: Eesti keel
Positsiooni asukoht: Tallinn (täpsemad detailid lepitakse kokku intervjuu ajal)

Põhiülesanded programmi ajal:

  • Välja eraldada ja analüüsida tarkvarasüsteemide nõudmisi ja tarkvarasüsteemide vastavat disaini
  • Visandada tarkvaraprojekti plaani ning monitoorida projekti käiku
  • Disainida tarkvara arhitektuuri, mis on samal tasemel ettevõtte strateegia, struktuuri ja protsessidega
  • Uudsel tehnoloogial baseeruv palgaarvestuse programmi prototüübi loomine koostöös ettevõttega

Potentsiaalsed uurimissuunad:
Olemasolevate tarkvaralahenduste ja uute tehnoloogiate analüüs ning selle põhjal palgaarvestuse programmi prototüübi Soome turule.

Ettevõtte X-faktor:
Previser on raamatupidamise ettevõtte pakkudes raamatupidamise teenust Soomes tegutsevatele ettevõtetele. Peakontor asub meil Tallinnas ning samuti on kontor ka Soomes, Vantaas. On mitmeid ettevõtteid kes sama teenust pakuvad, kuid meie eripära seisneb pikaajalistel teadmistel ning reaalsel kogemusel. Previser OÜ on siiani Eestis ainuke, kes teeb koolitusi nii eesti kui vene keeles praktilisest Soome raamatupidamisest, rõhk sõnal praktiline. Sinu abiga saame viia ettevõtte uuele tasemele!

Juhendaja:
Eve Bork, ettevõtte juht

Ootused kandidaadile:

  • Oled huvitatud palgaarvestuse tarkvarast ning selle loomisest
  • Oled meeskonnamängija
  • Oled uudishimulik ning tahad õppida uusi asju
  • Sul on hea iseseisva töö oskus

Websitewww.reach-u.com/
Business domain: Location-based Solutions and GIS
Working language: English. Knowledge of Estonian is useful, but not mandatory.
Position location: Tartu

Main tasks during the programme:

  • Designing, programming, and evaluating algorithms for various tasks (e.g. data mining algorithms, reports, visuals)
  • Self-development (i.e., reading papers on various scientific topics) and presenting findings to team members)
  • Documenting tasks

Directions for thesis research area:

  • Lookalike audience detection - Determine a set of users that resemble another group. o Keywords: big data, location, data analysis, machine learning
  • Human mobility analysis from mobile positioning data for smart-city and location-based advertising scenarios. o Keywords: human mobility patterns, trajectories, transport mode detection, location accuracy
  • Visualization of spatio-temporal data o Keywords: spatio-temporal data, visualization algorithms, visualization effectiveness and cognitive tasks experiments

Company's X-Factor:
Reach-U is one of the pioneers that joined the Industrial Master's Programme in IT back in 2017 and has been supporting the programme ever since. Joining the Industrial Master's Programme in IT with Reach-U will be easy for you and the company, since the know-how of what a student-life looks like is there. Plus, Reach-U is a company with a long history that values scientific approach in its work.

Supervisor:
Toivo Vajakas, Data Science expert with MSc in applied math. PhD student in informatics and mathematics. Interests: statistical models of spatio-temporal data, visualization, hi-performance computing.

Expectations for the applicant:

  • Common programming languages (Java, Python)
  • Version control systems (Git, SVN)
  • The following are a strong plus:
  • Prior experience with machine learning
  • Knowledge of statistics and Bayesian statistics
  • Strong analytical & visual thinking

Kodulehtwww.rappin.ee
Äridomeen: Vanapaberist nurgaprofiilide tootmine
Töökeel: Eesti keel, inglise keel vastavalt vajadusele
Positsiooni asukoht: Tartu, Räpina (detailsem kokkulepe intervjuul)

Põhiülesanded programmi ajal:

  • Andmekogumise eesmärgistamine, koguvate andmete kaardistamine (kas, kus, kuidas ja mida kogutakse), muudatuste ettepanekud
  • Andmete ettevalmistamise ja analüüsi teostamine
  • Masinõppe tööriistade ja meetodite rakendamine äriprobleemide lahendamiseks

Potentsiaalsed uurimussuunad:

  • Andmepõhine ärianalüüs
  • Masinõppe rakendamine
  • Tööstus 4.0 teemaatika: ennetav vs ennustav hooldus  masinate automaatseadistus, automaatmõõtmine jms või mõni muu just Sulle huvipakkuv uurimussuund, mis on seotud äriprotsessi valdkonnaga

Ettevõtte X-faktor:
Liitudes IT-tööstusmagsitrantuuri programmis Räpina Paberivabriku ning Tartu digiinnovatsioonikeskuse positsiooniga saad osaks millestki täiesti unikaalsest, sest tegemist on pilootprojektiga, mille tulemusena kajastame Sinu tegemisi väga paljudes kanalites ning oleme toeks igal sammul. Räpina Paberivabrik on keskkonnasõbralik ja stabiilselt arenev kaasaegne rahvusvahelise haardega ettevõte, kes austab paberitootmise traditsioone ja ajalugu. Tartu digiinnovatsioonikeskus on osa üleeuroopalisest DIH-võrgustikust, mida veab eest Tartu Ülikooli arvutiteaduse instituut.

Juhendaja:
Sind juhendavad arvutiteaduse instituudi infosüsteemide dotsent ning ettevõtte juhataja, Mihkel Peedimaa.

Ootused kandidaadile:

  • Masinõpe ja andmeteadus on sinu kirg
  • Oled süsteemne ning hea analüüsivõimega
  • Oled uudishimulik ning tahad õppida uusi asju

Websitewww.singularitycreations.ee
Business domain: Developing online services and informations systems
Working language: English
Position location: Tartu

Main tasks during the programme:
Participate in building highly scalable microservices based video production automation product for online market. Take part in the entire development cycle. Opportunity to lead smaller projects or taking the role of product owner. Alternatively dive into both front- and backend coding and database design (JavaScript – nodejs, GraphQL, Vue.js, MySQL, PostgeSQL).

Directions for thesis ressearch area:

  • Video production automation innovation
  • Developing a deployment strategy for microservices based application

Company's X-Factor:
Singularity Creations offers You a smaller team, thanks to witch things are very agile and our team works very efficient.

Supervisor:
Madis Kapsi (CTO) with his more than 10 years of coding experience, Madis has vast knowledge in the field. You will get a chance to build tools today that will redefine our tomorrow in video industry.

Expectations for the applicant:

  • Familiar with software development tools and technologies (back-end/front-end development basics)
  • Team player who wants to contribute and learn, interests in possible leadership role
  • Basic understanding of microservices and curiosity to expand that knowledge
  • Good communication skills

Websitewww.stacc.ee
Business domain: Data Science
Working language: English. Knowledge of Estonian is useful, but not mandatory
Position location: Tartu (UT Delta centre)

Main tasks during the programme:

  • Analysis and preparation of the data
  • Application of machine learning tools to solve business problems
  • Interpretation and communication of results to the business or project manager
  • Development of data driven products

Directions for thesis ressearch area:

  • Demand forecasting models
  • Recommendation systems for e-commerce
  • Natural language processing
  • Data driven business analysis

Company's X-Factor:
STACC (Software Technology and Applications Competence Center) is a research and development organization established in 2009 to conduct high-level applied research. As a leading machine learning center we work in cooperation with scientific and industrial partners. Our team consists of experts in the field with focus on applied machine learning and business projects. We use Python tools and pipelines, cloud computing and real-time APIs to deploy our models. Join our team and help us shape the AI landscape in Estonia.

Supervisor:
Eerik Muuli (MSc, PhD candidate at University of Tartu). Eerik Muuli is a software developer at STACC. He has worked with a wide range of practical machine learning problems, including data pipelines, monitoring systems, real-time APIs, and cloud infrastructure deployments.

Expectations for the applicant:

  • Experience with Python
  • Basic experience with Git and Linux
  • Data science and machine learning enthusiast
  • Extra points: Kaggle experience

Kodulehtwww.stagnationlab.com
Äridomeen: Designing and building digital experiences
Töökeel: Estonian
Positsiooni asukoht: Tartu

Põhiülesanded programmi ajal:
Kokkuleppel

Potentsiaalsed uurimussuunad:

  • Effective GraphQL API design
  • Write once, deploy everywhere mobile solutions (Hybrid; Flutter; React Native)
  • Tooling for React/Typescript/GraphQL ecosystem
  • Replacing native apps with new web technologies

Ettevõtte X-faktor:
Stagnation Lab tegeleb veebitehnoloogiatel põhinevate keerukate erilahenduste loomisega.Kuue tegevusaasta sisse on jäänud meil mitmeid ämbrite kolistamisi, aga eelkõige lahedaid õppetunde ning eriti hästi välja tulnud lahendusi, näiteks Smart-ID rakendus, Telia TV telerite ja digibokside rakendused, Klarvinduer eritellimusel tehtud e-poe platvorm ja Dag Coin Extended Universe kogu ökosüsteem. Oleme oma viieliikmelist punti kasvatanud tänaseks mitu korda. Meiega on liitunud inimesi, kellele meeldib võtta ette tehniliselt keerukaid väljakutseid ning luua kliendile parimaid lahendusi. Kasutame moodsaid tehnoloogiaid ja hindame loodud lahenduste elegantsust. Järgime agiilse arenduse ja terve talupoja mõistuse põhimõtteid.
Meie igapäevased tööriistad on:

  • Backend: Node.js, GraphQL, TypeScript
  • Frontend: React, TypeScript
  • Mobiil: iOS, Android, Hybrid, React Native
  • Testimine: Jest, Cypress
  • Andmebaasid: MySQL, Postgres

Juhendaja:
Taavi Sangel ja Priit Kallas

Ootused kandidaadile:

  • Huvi veebirakenduste loomise vastu
  • Tahe õppida uusi asju ja viimaseid tehnoloogiaid
  • Boonuseks on praktiline kogemus eelnevalt mainitud tehnoloogiatega

Kodulehtwww.stagnationlab.com
Äridomeen: Designing and building digital experiences
Töökeel: Estonian
Positsiooni asukoht: Tartu

Põhiülesanded programmi ajal:
Kokkuleppel

Potentsiaalsed uurimussuunad:

  • Effective GraphQL API design
  • Write once, deploy everywhere mobile solutions (Hybrid; Flutter; React Native)
  • Tooling for React/Typescript/GraphQL ecosystem
  • Replacing native apps with new web technologies

Ettevõtte X-faktor:
Stagnation Lab tegeleb veebitehnoloogiatel põhinevate keerukate erilahenduste loomisega.Kuue tegevusaasta sisse on jäänud meil mitmeid ämbrite kolistamisi, aga eelkõige lahedaid õppetunde ning eriti hästi välja tulnud lahendusi, näiteks Smart-ID rakendus, Telia TV telerite ja digibokside rakendused, Klarvinduer eritellimusel tehtud e-poe platvorm ja Dag Coin Extended Universe kogu ökosüsteem. Oleme oma viieliikmelist punti kasvatanud tänaseks mitu korda. Meiega on liitunud inimesi, kellele meeldib võtta ette tehniliselt keerukaid väljakutseid ning luua kliendile parimaid lahendusi. Kasutame moodsaid tehnoloogiaid ja hindame loodud lahenduste elegantsust. Järgime agiilse arenduse ja terve talupoja mõistuse põhimõtteid.
Meie igapäevased tööriistad on:

  • Backend: Node.js, GraphQL, TypeScript
  • Frontend: React, TypeScript
  • Mobiil: iOS, Android, Hybrid, React Native
  • Testimine: Jest, Cypress
  • Andmebaasid: MySQL, Postgres

Juhendaja:
Taavi Sangel ja Priit Kallas

Ootused kandidaadile:

  • Huvi veebirakenduste loomise vastu
  • Tahe õppida uusi asju ja viimaseid tehnoloogiaid
  • Boonuseks on praktiline kogemus eelnevalt mainitud tehnoloogiatega

Websitewww.stat.ee
Business domain: Statistics, Data Science
Working language: English/Estonian
Position location: Tartu, Tallinn or Viljandi (agreed during the interview)

Main tasks during the programme:
Apply machine learning methods for data editing and imputation on real survey data.
Currently we are doing quite a lot data editing to improve quality of survey data. Experiences of another countries are shown that machine learning methods can reduce manual work a lot. We have several different datasets with manual edited data that could be used in this project. Expected outcome is set up editing and imputation program that can be modified and used in different works.

Directions for thesis ressearch area:

  • Machine learning
  • Statistical analysis

Company's X-Factor:
Statistics Estonia has the most diverse datasets in Estonia, which offers many different ways of analyzing them. We have high professionals working in Statistics Estonia from whom you can learn a lot and discuss together. In Statistics Estonia you can contribute to the development of data science so that the decision makers can make wiser decisions for the development of the society.

Supervisor:
Kristi Lehto, head of methodology team, MSc in Mathematical Statistics (University of Tartu). She has more than ten years of experience in official statistics.

Expectations for the applicant:

  • Good knowledge of R
  • High motivation to achieve results
  • Statistical background is an advantage, but not a necessity

Websitewww.telia.ee/
Business domain: Telia TV service
Working language: Estonian/English
Position location: Tartu

Main tasks during the programme:
In this role Your responsibilities are developing and improving TV applications including the use of automated developer tools. Our DevOps team is the technology partner for business owners, responsible for developing and maintaining TV services and systems.

Directions for thesis ressearch area:

  • User behavior tracking ja analytics
  • TV screen messaging UX improvements
  • Ad engine implementation

Company's X-Factor:
Telia TV DevOps team is capable to handle all developments for Telia TV services and maintain it 24/7 In this role You often have to find and support balance between beauty and performance, frontend and backend, testability and code-base sustainability. What can be more challenging! With us You are part of the friendly and supportive team with various competences. At the same time no role is carved into the stone and initiatives towards other areas are highly recommended. You have access to develop features and applications, used by significant number of Estonian people every day. It’s a workplace where You can deal both with code developments and self-development. For that You have only to dare and care!

Supervisor:
Peeter Kask (leading developer and mentor), Kairi Meister (direct manager)

Expectations for the applicant:

  • You are interested on software developing through the whole lifecycle
  • You are curious to understand things on deeper level
  • You have rather good communication skills in order to become an excellent team player
  • You dare to show initiative and You are willing to plan Your daily job activities by Yourself
  • You have experience or basic skills as JavaScript developer
  • You will have to deal with:
  • JavaScript and HTML5 (React)
  • Android and iOS apps (React Native)
  • Linux and Set Top Boxes

PS. Set Top Box is just a tiny Linux computer with TV UI running on fullscreen browser window. Technically, it is a JS web application where memory usage and performance aspects cannot be underrated.

Websitehttps://threod.com/
Business domain: Space Technology – Unmanned Aerial Systems
Working language: English/Estonian
Position location: Tallinn (details will be agreed during the interview)

Main tasks during the programme:

  • Design and develop embedded software/firmware for 32bit microcontrollers (using the C language)
  • Develop closed-loop digital control systems for an industrial environment, including microcontroller-based instrumentation and motor controls
  • Test and debug firmware on hardware platforms
  • Work with hardware engineers and purchasing to select hardware components
  • Create PC-based software tools for product testing, updating or configuration
  • Maintain code in repository using revision control tools
  • Support research and development efforts relating to ultrasonic, infrared and other sensor technologies
  • Support product connectivity over industrial networks such as Ethernet/IP, Modbus TCP and CAN
  • Document product features and functionality

Directions for thesis ressearch area:

  • Machine Learning and Training AI for Visual Object Recognizing
  • Sensor Fusion

Company's X-Factor:
Threod Systems is the leading developer and manufacturer of Unmanned Aerial Systems. In our headquarter in Estonia we have built a team who continues the tradition of quality, innovation and service our customers depend on.

Supervisor:
Once you join the Industrial Master’s Programme in IT at Threod Systems, you will be supervised by Ville Vellend, who has more than 30 years software development experience in every possible aspect and angle. Ville has spent the last ten years mostly with Unmanned Aerial Systems development. Under his supervision you will be guided through digital aerospace universe.

Expectations for the applicant:

  • Experience in Embedded C Programming. Ability to write clean and documented code.
  • Interest in technology, cooperation orientation, good communication skills and willingness to contribute to Threod’s success in an unmanned aerial systems area as part of the programme.
  • You would be essentially working part-time in all of our R&D engineering teams and see what makes us tick up close

Websitehttps://biit.cs.ut.ee
Business domain: Precision medicine, bioinformatics
Working language: English/Estonian
Position location: Tartu (Delta centre)

Main tasks during the programme:
Developing the bioinformatics approaches and pipelines for genetic variant depending drug prescriptions (pharmacogenetics).

Directions for thesis ressearch area:
In this research, we will develop the computational pipeline to identify specific genetic variants linked to potential harmful side effects for drugs. Many variants are indicated on drug labels but they have not been available to doctors at the moment of prescription. Developing a database of such variants and computational pipeline for their detection is the main task.

Company's X-Factor:
You will be involved in the world’s first ever deployment of such pharmacogenetics predictions on national IT infrastructure. The team is about 10 people from IT, bioinformatics, genetics backgrounds. This project is of very high international interest.

Supervisor:
Prof Jaak Vilo and Research Fellow Sulev Reisberg, PhD

Expectations for the applicant:
The student should have excellent programming skills in Python and SQL, possibly also R. Interest in bioinformatics and health data is a must. Motivation to further obtain a PhD is a great plus.

Websitehttps://biit.cs.ut.ee
Business domain: Precision medicine, bioinformatics
Working language: English/Estonian
Position location: Tartu (Delta centre)

Main tasks during the programme:
Developing the bioinformatics approaches and pipelines for genetic variant depending drug prescriptions (pharmacogenetics).

Directions for thesis ressearch area:
In this research, we will develop the computational pipeline to identify specific genetic variants linked to potential harmful side effects for drugs. Many variants are indicated on drug labels but they have not been available to doctors at the moment of prescription. Developing a database of such variants and computational pipeline for their detection is the main task.

Company's X-Factor:
You will be involved in the world’s first ever deployment of such pharmacogenetics predictions on national IT infrastructure. The team is about 10 people from IT, bioinformatics, genetics backgrounds. This project is of very high international interest.

Supervisor:
Prof Jaak Vilo and Research Fellow Sulev Reisberg, PhD

Expectations for the applicant:
The student should have excellent programming skills in Python and SQL, possibly also R. Interest in bioinformatics and health data is a must. Motivation to further obtain a PhD is a great plus.

Websitewww.ims.ut.ee
Business domain: Human-Vehicle Interaction
Working language: English/Estonian
Position location: Tartu (Delta centre)

Main tasks during the programme:
Validating the state-of-the art in robotics and driverless vehicles; developing software; reading academic papers.

Directions for thesis ressearch area:

  • Robotics and driverless vehicles
  • Human-vehicle interaction modalities
  • Trust in autonomous driving

Company's X-Factor:
You will be involved in the project with several Industrial Master's in IT students, which will make your experience definitely more fun. Plus, your tasks will be related to collaboration between Bolt and UniTartu (https://www.ut.ee/en/news/bolt-kicks-self-driving-technology-research-pa...), which will give you an experience of a real R&D project.

Supervisor:
Assoc. Prof. Karl Kruusamäe and PhD Alexander Nolte

Expectations for the applicant:

  • Passion for writing software;
  • Eager for testing out new technologies;
  • Interest in conducting cutting edge research in an exciting new environment;
  • Excellent English skills for reading and understanding academic papers;
  • Self-motivated

Websitewww.tuit.ut.ee/et/teadus/arun-kumar-singhhttps://sisu.ut.ee/collabrobotics/home-0
Business domain: Robotics, Machine Learning
Working language: English/Estonian
Position location: Tartu (Delta centre)

Main tasks during the programme:
Setting up the experimental platform with autonomous driving simulators like CARLA to record driving behaviors in the form of trajectories.
Developing computational models to learn and predict driving actions in a given road scene.

Directions for thesis ressearch area:
In this research, we would adopt a data driven approach to learn and predict human driving behaviors. The main idea is to record human driving behavior on simulators and subsequently apply techniques like Inverse Reinforcement learning to develop computational models for human driving behavior.

Company's X-Factor:
You will be involved in the project with several Industrial Master's in IT students, which will make your experience definitely more fun. Plus, your tasks will be related to collaboration between Bolt and UniTartu (https://www.ut.ee/en/news/bolt-kicks-self-driving-technology-research-pa...), which will give you an experience of a real R&D project.

Supervisor:
Assoc. Prof. Arun Kumar Singh

Expectations for the applicant:
The student should have excellent programming skills in C++ and Python, etc. and moderate to good mathematical skills in topics like linear algebra, probability and machine learning. Prior robotics experience would be an advantage.

Website: ml.cs.ut.ee
Business domain: Safety in Autonomous Driving
Working language: English/Estonian
Position location: Tartu (Delta centre)

Main tasks during the programme:

  • Implementing state-of-the art methods relating to uncertainty estimation, sensor data analysis and path planning
  • Developing software
  • Reading academic papers

Directions for thesis ressearch area:

  • Safety in autonomous driving
  • Uncertainty estimation
  • Calibration in machine learning

Company's X-Factor:
You will be involved in the project with several Industrial Master's in IT students, which will make your experience definitely more fun. Plus, your tasks will be related to collaboration between Bolt and UniTartu (https://www.ut.ee/en/news/bolt-kicks-self-driving-technology-research-pa...), which will give you an experience of a real R&D project.

Supervisor:
Assoc. Prof. Meelis Kull

Expectations for the applicant:

  • Strong mathematical and programming skills
  • Experience in software development
  • Passion for new technologies
  • Interest in conducting cutting edge research
  • Excellent English skills for reading and understanding academic papers

Website: www.perkinelmer.com/ and https://biit.cs.ut.ee/
Business domain: Microscopy Image Analysis
Working language: English
Position location: Tartu (Delta centre)

  • Main tasks during the programme:
  • Exploratory analysis of the imaging data
  • Training various Neural Networks using different training strategies
  • Evaluation of trained models on independent data
  • Hyperparameter tuning
  • Presentation of the results to supervisors and the team members
  • Active participation in discussions

Directions for thesis ressearch area:

  • Segmentation of cells and cellular structures from microscopy images
  • Improving resolution of microscopy images
  • Analysing transferability of networks trained on one data set to another

Company's X-Factor:
This position is created within a R&D project that ICS academic staff is working on. Joining this project you will give you an advantage of easily managing your studies, as even the location of the position is in the same building with your academic studies.

Supervisor:
Leopold Parts (University of Tartu, Wellcome Sanger Institute) and Dmytro Fishman (University of Tartu). Supervisor from industrial partner's side: Kaupo Palo (PerkinElmer).

Expectations for the applicant:

  • Strong Python programming skills
  • Strong math and stats knowledge
  • Some experience or background in machine learning is a plus (but not obligatory)
  • Some background in computer vision is a plus (but not obligatory)
  • No biological background is needed, but a little enthusiasm about biology/medicine would be helpful
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