Kandideeri ITTM-i

Mõtled kandideerida IT-tööstusmagistrantuuri? Tore kuulda! Pea silmas järgnevat:

programmi võivad kandideerida 1. aasta magistritudengid informaatika, tarkvaratehnika, andmeteaduse ja IT mitteinformaatikutele õppekavadelt;
programmis osalemiseks pead olema järjel, et lõpetada oma õpingud nominaalajaga;
saad kandideerida kuni kahele positsioonile;
kui kandideerimine läheb hästi ja alustad reaalselt programmiga, pead oma teistest stipendiumitest lahti ütlema.

Pikemalt loe programmist siit. 21.03.23 toimunud infoseminari salvestust saab vaadata siit.

Kandideerimise ajakava

Etapp	Mis toimub?	Periood
I kandideerimisvoor	Saad kandideerida kahele positsioonile. Esitada tuleb CV, vastused partneri püstitatud küsimustele ja prooviülesande lahendus, kui positsioon seda eeldab.	27.03–09.04
II kandideerimisvoor	Partnerid kutsuvad sind vestlustele ja intervjuudele, et omavahelisest klapist aru saada.	17.04–14.05
Lepingute sõlmimine	Kui klapp on hea, siis saame sõlmida kolmepoolse lepingu, millega oled ametlikult programmi vastu võetud!	mai–juuni
Programmi algus	Programmi täpne algus lepitakse kokku nii, et see sobiks nii sinule kui partnerettevõttele. Kindlasti leitakse aega, et saaksid suvel ka puhata.	juuni–juuli

Programmipositsioonid '23

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 in the Delta building or from distance.
Language	Speaking English is required
General assignments	Developing various analytics and machine learning solutions that help us: forecast production and consumption; decide what the most cost-effective way to distribute energy would be.
Directions for thesis	Time-series prediction Supervised machine learning Optimization
Expectations for applicant	Data wrangling in Python Elementary know-how on time-series prediction and supervised learning
Supervisor(s)	Kristjan Eljand, Technology Scout
Admission info	I round Solve this test task. II round We'll invite you to meet us.

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 optimally? Answering these questions will be your focus area. 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!

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.

Website	www.swedbank.ee/careers
Business domain	Financial services
Location	Tartu & Tallinn Hybrid work, with regular physical presence encouraged.
Language	English
General 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.
Directions for 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
Expectations for applicant	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(s)	Simon Whelan, Head of Data Science and Analytics Juan Manuel Lorenzo Varela, Team Manager in Data Science
Admission info	I round Why do you want to join Swedbank? Who or what inspired you to work in data science? 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. What do you want to achieve and learn working with Swedbank during the industrial master’s? II round We will have a series of virtual interviews to learn more about you and to test your data science skills.

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.

Pipedrive welcomes two students to join!

We are more than sure — Pipedrive doesn’t need any introduction. The first CRM to use Kanban to visualize sales, Pipedrive was founded in 2010 by five Estonian engineers and entrepreneurs, and in 2020 we became the 5th unicorn from Estonia.

Website	https://www.pipedrive.com/
Business domain	Software development (CRM & intelligent 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	English
General assignments	Software development and testing Working with microservices in cloud-based development environment Working in a team: taking part in planning, standups, retro meetings Cross-team collaboration Presentation and demonstration of new solutions, ideas, research findings
Directions for thesis	Generally we are open and are looking forward to fully utilizing your profile when choosing a topic for the thesis. Expect it to be in the next areas: CI/CD monitoring; DevOps assessment metrics; Analyzing user behavior and predicting account indicators; Applying machine learning / AI to different parts of our platform. Many more potential topics are available depending on your interests.
Expectations for applicant	Good communication skills Some programming skills Fun to work with :)
Supervisor(s)	Mykhailo Dorokhov, Engineering Learning & Development Lead As your supervisor, Mykhailo will take care that you are growing as an engineer and your goals at the university are aligned with what you do at Pipedrive. You will also get a buddy in the team you'll be working in and from whom you will be able to ask all kinds of technical questions.
Admission info	I round Why do you want to join Pipedrive? Please answer this in video! :) II round You must take a brief cognitive aptitude test. It is done online and won't take much time. The most well-suited candidates are then called for an interview.

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. Many of the program’s alumni are currently our employees, continuing their work at Pipedrive...

Don’t be shy — apply for a position!

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.

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	You can either be Estonian- or English-speaking
General assignments	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)
Directions for thesis	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
Expectations for applicant	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 method You do not need to have all of them, any abovementioned skill may be enough.
Supervisor(s)	Elis Kõivumägi, Project Manager (also a PhD student at UT) Teet Jagomägi, Product Owner … or someone else, depending on your profile
Admission info	I round Please describe your experience in free form (perhaps link to portfolio/github, if you have any). Describe briefly your motivation and explain, in which area you want to develop yourself. When looking back at your hobby projects or courses at the university, can you think of any “Wow!”, “Heureka!” or “I like that!” moments? If yes, please describe! II round We'll ask you to meet us — the goal is to test if we match. Maybe you also have three questions for us?

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!

Haut.AI is Estonian AI startup pioneering next-generation skincare. More than 80 companies, including Ulta and Beiersdorf, have used our SaaS toolkit to launch B2C applications, create personalized product journeys, and deliver on their sustainability commitments.

Website	www.haut.ai
Business domain	Software development
Location	Tallinn Remote or hybrid work is possible.
Language	English
General assignments	Clean and prepare data for model training Analyze and explore data Develop computer vision algorithms Write machine learning training pipelines Run machine learning pipelines Evaluate machine learning models Present modeling results Document model cards
Directions for thesis	Computer vision and deep learning for skincare
Expectations for applicant	We want you to: Be able to write a clear code in Python (pandas, numpy, scikit-learn, matplotlib, plotly, opencv) Be familiar with at least one DeepLearning Framework Have good understanding of basic computer vision algorithms Have advanced English
Supervisor(s)	Timur Tlyachev, Head of Data Science
Admission info	I round Who are you and what is your specialization? What do you expect from the program when joining Haut.AI? Describe your last/favorite project/homework related to data science and what part did you play in it? II round You can expect a virtual interview or face-to-face chat with coding exercises.

We at HautAI are excited to extend an invitation for you to join our team. Our company is dedicated to expanding knowledge and innovation in the IT industry, and we believe that our team of experts can provide a valuable learning experience for you.

Our team is comprised of individuals who are passionate about sharing their knowledge and helping others grow. You will have the opportunity to work alongside these experts and learn from their years of experience.

We look forward to the opportunity to work with you and help you achieve your professional goals!

Website	www.haut.ai
Business domain	Software development
Location	Tallinn Remote or hybrid work is possible.
Language	English
General assignments	Cleanse and prepare data for analysis Analyze and explore data Do ad-hoc reporting Develop analytical dashboards Interpret and analyze data using statistical techniques Prepare statistical reports Do data visualization Present results of analyses
Directions for thesis	Time-series analysis of skin conditions and consumer clustering based on skin conditions
Expectations for applicant	We want you to: Be able to write a clear code in Python (pandas, numpy, scikit-learn, matplotlib, plotly) Have good knowledge of SQL (PostgreSQL) Feel strong in mathematical statistics Be familiar with basic unsupervised ML algorithms Be familiar with data visualization approaches Have advanced English
Supervisor(s)	Timur Tlyachev, Head of Data Science
Admission info	I round Who are you and what is your specialization? What do you expect from the program when joining Haut.AI? Describe your last/favorite project/homework related to data science and what part did you play in it? II round You can expect a virtual interview or face-to-face chat with coding exercises.

We look forward to the opportunity to work with you and help you achieve your professional goals!

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 You'll be doing hybrid work.
Language	English
General 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
Directions for thesis	Multilingual text classification 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
Supervisor(s)	Maksim Butsenko, PhD, Staff Data Scientist
Admission info	I round What drew you to the specific topic you are applying for? 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? Can you describe a time when you worked collaboratively with a team to achieve a goal? What did you learn from the experience? Describe a machine learning project you've worked on in the past. What were the challenges you faced, and how did you overcome them? II round We want to have a video interview with you.

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.