Dear student! We invite you to take a step towards your future. University of Tartu Institute of Computer Science joins hands with prominent companies to combine cutting-edge education and practical work experience. Positions for next year will be revealed in the spring of 2025.


Past positions:

Positions for 2024

Company description

Reach-U, www.reach-u.com 

Data analysis platforms for telecommunications and media companies, optimization and profiling algorithms, data exploration user interfaces, geospatial data

IntroductionReach-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.
LocationReach-U is located in Tartu, hybrid work is common (remote individual + office teamwork).
LanguageMix of Estonian and English

Edit media


Expected assignment
  • 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)
Topics for master’s 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 methods

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


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

Why you should join us?

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.

Application process

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:


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



Company description

AS SEB Pank, Home Page | SEB


IntroductionSEB 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.
 Career | SEB
LocationSEB Tartu Innovation Centre in Delta building or Tallinn at SEB main office.
LanguageKnowledge of English is mandatory, knowledge of Estonian is a bonus. 
Expected 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
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
Expectations for applicant

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 

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
Bolt HQ


Company descriptionBolt 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. 
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 thesisWe 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 Applicant1. 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?
SupervisorCarlos Bentes, Senior Data Scientist
Why join us?

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:




Company descriptionEnefit / 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.

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…

LocationThere 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.
Expected assignment
  • Create features to make better predictions.
  • Deliver data analysis.
  • Share your code
  • Present your work.
  • Finally, integrate your model with developers.
Topics for master’s thesisProbabilistic (quantile) forecasting of electricity prices
Expectations for applicant
  • Good at mathematics, especially probability
  • Deep learning
  • Presentation skills
  • Interest for energy industry
SupervisorJean-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


  • 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.



Company descriptionSwedbank 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 domainFinancial services
LocationTallinn & Tartu, hybrid work, with regular physical presence encouraged
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
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, 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)

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.


Company descriptionPipedrive
Software development (CRM & intelligent revenue platform)

IntroductionWe are confident that Pipedrive needs no introduction. As the first CRM to employ Kanban for visualizing sales, Pipedrive was established in 2010 by five Estonian engineers and entrepreneurs. By 2020, it had become the fifth Estonian company to achieve unicorn status.
 See our introduction video. 
LocationTartu,  we expect your presence in the office. We hold the belief that face-to-face communication and physical presence are more effective during your initial months. Later on, it becomes possible to work remotely once you have gained confidence.
Expected assignment
  • Software development and testing
  • Working in a cloud-based development environment
  • Working in a team:
    • taking part in planning, standups, retro meetings
  • Cross-team collaboration
  • We don't expect but encourage you to come up with your
    own solutions, ideas, research findings
Topics for master’s thesis

Pipedrive has multiple initiatives that lean on disruptive approaches to solving problems. Depending on your interests, the following areas are hot:

  • Applying machine learning to different parts of our product
  • Continuous integration and continuous delivery metrics
  • Automated site reliability engineering
  • Actionable semantic search

But of course, there are also many other topics that could be available depending on your interests.

Expectations for applicant
  • Good communication skills
  • Ability to write code in any programming language
  • Be fun to work with
SupervisorMykhailo Dorokhov, Senior Engineering L&D Lead
As your supervisor, Mykhailo will take care that you are growing as an engineer and that your goals at university are aligned with what you do at Pipedrive. You will also get a buddy in the team you'll be working with, who will support you through your journey as a software engineering intern.
Why you should join us?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. We have recently launched the first AI-powered solutions in our product, and you'll have a chance to work together with people who do AI on enterprise level, and who knows, maybe even make your thesis in this area!
Application process

We have a simple three-step interview process:

Step 1. Every applicant must take a brief cognitive aptitude test. If you like logic puzzles - you'll love this one.
Step 2. Make a short 3-minute video introducing yourself, describing your previous studies/experience and telling us what made you apply to Pipedrive
Step 3. Interview with the internship manager, our engineers and TA partner. We don't bite, and it's your chance to see Tartu from the 16th floor.



Company descriptionCodemagic - CI/CD for mobile teams. DevOps. codemagic.io
IntroductionReleasing 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.
LocationCodemagic has a remote team working from different parts in EU, Africa, Middle East and Asia.

Candidate can choose to work remotely or we have desks available at our co-working space at Mobi Lab - Akadeemia 3, Tartu.
Expected assignmentsStudent 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.
Topics for master’s
For example:
● Language models in DevOps for mobile developers.
Expectations for applicantFor 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.