Applied Data Fellowship

The Applied Data Fellowship is a highly-selective, 12-month program based at the University of Chicago Harris School of Public Policy that embeds early career professionals with strong data skills into local government and nonprofit organizations across the United States. Fellows spend one year working to design and implement high-impact programs, helping translate data-driven insights into actionable policy recommendations, new programs, and operational changes for partner organizations. The program focuses on the intersection of data analysis and public policy. Fellows work on tailored projects that may include analyzing complex datasets through advanced statistical modeling and forecasting, visualizing insights, engineering high-integrity data architecture, deploying machine learning models and LLM integrations, and translating legislative requirements into service delivery. In addition to hands-on experience implementing data insights and working closely with senior-level stakeholders, Fellows receive managerial oversight, mentorship, and technical support in the form of data analysis training and oversight. The program is open to graduates from across divisions at the University of Chicago and selects from a national pool of over 1,200 applicants annually.