MS in Data Science
Industry Partnerships

Where education and industry come together to shape tomorrow’s workforce.

The UConn MSDS program is an intensive, 11 month pre-professional program designed to equip students with the core skills needed for a career in data science. Students come to the program from a variety of backgrounds, including computer science, applied math, statistics, economics, biology, and business. Students take core courses in Applied Statistics and Statistical Computing, Machine Learning Algorithms and Data Mining and Management, as well as courses in Ethics, Visualization and Communication, and Research Design. The program ends with a project-based capstone course.

Get Involved with UConn's MS in Data Science

Aligning our program with industry needs is key to our students’ success, while our students bring their training and diverse preparation to industry. To maintain this close connection, our program relies on industry interaction. There are a number of ways your company can work with our program that will benefit you and help our students.

To discuss any of the opportunities below, contact Jeremy Teitelbaum, the Director of the program.

How Industry Partners Help

Give a talk or meet with students

The simplest way to get involved is to give a talk to our students, either online or in person. Possible topics for such a talk include:

  • an overview of your career path into data science
  • a description of how your company relies on data science to add value to your business
  • some of the new tools or techniques your company is using or considering
  • a look into the hiring process for data scientists at your company – what do you look for? what skills are important?
  • a talk about a particular problem and what techniques your company used to solve it.

Our students are always eager to hear from professionals in the field and appreciate the opportunity to ask them questions.

Sponsor a short-term project or “hackathon”

A “hackathon” project is a small, self-contained project that can be done over the course of a weekend or perhaps two weekends with the week in-between. For students, the project would be optional but would give them a chance to try their hand at something concrete. For your company, this would be a chance to get an early look at the students in the program and maybe learn something about the particular problem you pose.

To sponsor a hackathon, you would need to provide:

  • a clear description of the goals of the project.
  • a dataset or instructions on how to obtain the relevant data.
  • a description of expectations for a final report.

You would also need to identify a contact person at your company who could work with us to distribute the information to our students and answer questions that might come up, and, at the end of the project, make an assessment of the students’ work.

Sponsor a Capstone Project

The Capstone course runs during May and June, ending the first week in July. Every student in the program is required to participate. We operate as a consulting data science group; your company outlines the problem, provides the data, and receives a professional analysis responding to specifications you supply. Given the students training and their varying background we can provide real value to your company. At present there is no cost associated with sponsoring a capstone project.

We would assign multiple groups of students to the same project, creating the opportunity for the development of different approaches to your problem.

The program can sign an NDA to protect the confidentiality of the data and will do our best to meet your requirements. We have not worked with truly confidential or proprietary data, so we have hosted the data on our own servers and allowed students to work on their own laptops, but we do commit to keeping the data off public clouds and to destroying everything at the conclusion of the project. If the data requires a more stringent security regime we would have to discuss how to handle that.

The goal of this project is to be realistic. We expect all of the usual issues in a data science project to arise, and in particular the need to clean the data. Dealing with such issues is part of the challenge for the students. The capstone project is led by a UConn faculty member. The timeline for a capstone project is as follows:

  • In March, we would begin discussions with a contact at your firm, formulating the project specifications, discussing any NDA parameters, and addressing technical considerations such as transferring and hosting the data or gaining API access.
  • During April we would agree on any NDA terms. Late in April there would be an initial meeting between the students and a representative from your firm, where you would provide background on the project and lay out expectations.
  • By the beginning of May we would have identified the student groups, secured any NDA agreements, and settled any technical issues regarding access to the data.
  • During the second week of May there would be a formal kick-off meeting with a representative from your company and the students in which you would talk more specifically about the data and the project goals. (1.5 hours)
  • At the end of May there would be a follow-up meeting at which students could ask questions and talk about issues that may have arisen so far. (1.5 hours)
  • In mid-June there would be a second check-in meeting. (1.5 hours)
  • After the July 4th Holiday, the students would present their conclusions to the client. (3 hours)

In terms of time commitment by the company, assuming that the technical issues are not overly complicated, we would need about 3 days of time over the 3-4 month period March-June.

Sponsor a (paid) intern

Our students focus is on getting a job, and an internship is one of the most valuable experiences they can have. We can arrange for paid internships that also earn credit in our program.

More generally, we can discuss a pipeline program or on-campus interview day so that your company can meet our students and see what they have to offer.

Hire our graduates - This is the very best thing!


Jeremy Teitelbaum
Director, MS in Data Science Program
University of Connecticut

Application Deadline

Spring 2024: 
Applications open September 2023

Overall job growth - 10 years

Median Salary

professional, scientific and technical service top industry jobs

Labor Insight:  Source: U.S. Department of Labor Statistics, 2022.