Become a DSSG Summer Fellow!
The Data Science for Social Good Summer Fellowship is a full-time, 12-week summer fellowship at Carnegie Mellon University. The fellowship is a project-based training program designed to train responsible data scientists and ML/AI practitioners with strong skills in solving real-world social impact problems in collaboration with governments and non-profits and an understanding, excitement, and passion for solving problems with social impact.
Successful fellows have different skill profiles and backgrounds in order to create a collaborative community. Everyone has some programming, statistics and data analysis skills in addition to a passion for making a social impact. Some are stronger at Computer Science and Machine Learning. Others have a strong Applied Math or Statistics background. Some come from a quantitative Social Science, Economics, or Public Policy background. Others have Physics or Chemistry or Geography or Linguistics degrees. We’re not expecting you to be awesome at everything. Tell us what you’re good at and what you’d like to learn. In addition, personality and communication skills matter! If you’re passionate about a cause or social issue, tell us about it in your application. If there’s a recent project you’ve done that you’re proud of, we’d like to hear about it.
All fellows are expected to attend the entirety of the fellowship in person. There will be no remote option for participating in the program. Fellows are paid a stipend for participating in the program that is more than enough to cover travel, housing, and other expenses for the summer.
The program is designed for current students and recent graduates, and has accepted current undergraduate and graduate students, post-docs, as well as recent graduates who are currently working.
The program accepts U.S. citizens and non-U.S. citizens, including those with F-1 visas, and has sponsored J-1 visas.
For further questions, please see our FAQs.
There are 3 steps to the application process, and we encourage you to complete them as soon as possible:
- Application Form Part 1: Please submit Part 1 of the application as soon as possible.
- Application Form Part 2: Once you submit Part 1, you will get a personalized link to Part 2 of the application which will include more details about your skills and background.
- Recommendation Letters: You will get a personalized URL to a recommendation letter form. Please make sure to send that to your references and ask them to fill it out by the deadline.