The Data Science for Social Good Fellowship (DSSG) is a hands-on and project-based summer program that launched in 2013 at the University of Chicago and has now expanded to multiple locations globally. It brings data science fellows from across the world to work on machine learning, artificial intelligence, and data science projects that have a social impact. From a pool of typically over 800 applicants, 20-40 fellows are selected from diverse computational and quantitative disciplines including computer science, statistics, math, engineering, sociology, economics, and public policy backgrounds.

The fellows work in small, cross-disciplinary teams on social good projects spanning education, health, energy, transportation, criminal justice, social services, economic development and international development in collaboration with global government agencies and non-profits. This work is done under close and hands-on mentorship from full-time, dedicated data science mentors as well as dedicated project managers, with industry experience. The result is highly trained fellows, improved data science capacity of the social good organization, and a high quality data science project that is ready for field trial and implementation, delivered at the end of the program.

In addition to hands-on project-based training, the summer program also consists of workshops, tutorials, and discussion groups based on our data science for social good curriculum designed to train the fellows in doing practical data science and artificial intelligence for social impact.