Jason Goodman (He/Him) is a student analyst supporting the Digital Benefits Network team’s work on Rules as Code at Georgetown’s Beeck Center for Social Impact + Innovation. Goodman is contributing to a prototype to explore the use of large language models in translating benefits eligibility policy into code and between coding languages.

Goodman is currently pursuing a dual Master of Public Policy and Master of Business Administration at Georgetown‘s McCourt School of Public Policy and McDonough School of Business. Prior to attending Georgetown, Goodman worked as a senior product manager in the tech sector and launched products that benefited hundreds of organizations and individuals. He has an engineering background and holds a bachelor’s degree in Electrical Engineering and Computer Sciences from the University of California, Berkeley.

Goodman is passionate about combining his engineering background with his policy training to develop more equitable and accessible benefits systems. To that end, he is also a Digital Governance Research Fellow in the McCourt School’s Better Government Lab. Goodman is currently based in Washington, DC.