Information for Potential Partners

In Fall 2023, the MA Economics Program at UT-Austin launched a new practicum course focusing on data science projects. Throughout this semester-long course, instructor Edward Krueger mentors students working in small groups on projects selected by industry partners. This practicum serves as a capstone option for our students and offers our industry partners 14-weeks of support on a data-driven project. It can also serve as a pipeline for new graduate recruitment.

The student consultants will typically be in their second year of the MA Economics program and will have completed coursework such as “Python, Databases and Big Data Analytics,” “Data Mining and Statistical Learning,” “Causal Inference,” and/or “Time Series Econometrics,” in addition to their required economics coursework. Many students also have 1+ year of industry experience before entering our program. We assign students to groups based on their interests, but we also consider company preferences and technical requirements.

Project Topics:

We’re interested in projects where students can leverage their skills in Python, SQL, ML, etc. Projects containing in-depth data analysis, analytics software POCs, dashboards, data engineering pipelines, or ML/AI would all be great fits. For example, in the past, a fast-moving consumer goods company asked our student team to conduct a shopper loyalty analysis and to develop a predictive model of customer churn. We are open to any project that leverages your data to generate strategic insights while enhancing student experiential learning.

Company Commitments:

We recognize that data teams are typically under a lot of pressure, so we want to keep your involvement manageable. Our expectations from companies are:

• A project document that scopes out the project’s purpose, expected deliverables, documents the data sources (and, if applicable, how to access them), any existing code bases the students will work with, relevant processes, etc. While the scope of the project may be adjusted during the first few weeks of engagement, we require that all necessary data be made available to Edward Krueger by August 15 in order to ensure project viability.
• Limited touchpoints throughout the semester. We’ll start with a kickoff call with the instructor and student team. If your company has a presence in Austin, we can hold this meeting in person, but are also happy to work remotely. In mid-October, the team will prepare a remote/virtual midterm presentation and receive feedback from your team.  Final presentations will take place either in-person or remotely at the end of the semester, with all work completed and final deliverables due no later than December 5, 2024 (the last day of the Fall semester).
• A point of contact for questions that may arise during the semester, communicating either through email or our course’s Discord server (similar to Slack).

Our other request is that our students be able to make some (redacted) portions of the project public. This could be a report explaining the work, some portion of the code, visualizations, a simplified POC, etc. We are aware that this will vary with the nature and sensitivity of projects and data. We also ask that we be able to use your company name; this makes our students more marketable and allows us to grow the program for future cohorts.

Restrictions: For-profit clients need to be revenue-generating, in existence for at least two years, and have at least 5 employees.  Non-profit clients must be 501(c)3 organizations for at least 3 years and have a minimum of 3 paid employees. We prefer to not take start-ups or companies that utilize outsourced teams for data management. We evaluate projects based on the following: 

• Does it interest students?
• Does it develop their data science skill set?
• Does it create job opportunities? (There is no expectation of future employment with your organization, but we are looking for projects that will enhance our students’ resumes.)