Jason Goodman (he/him) is a Student Analyst supporting the Digital Benefits Network (DBN) team’s work on Rules as Code at the Beeck Center for Social Impact + Innovation at Georgetown University. Jason is contributing to a prototype to explore the use of Large Language Models (LLMs) in translating benefits eligiblity policy into code and between coding languages.

Jason 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, Jason worked as a senior product manager in the tech sector and launched products that benefitted hundreds of organizations and individuals. He has an engineering background and holds a Bachelor’s degree in Electrical Engineering and Computer Sciences from UC Berkeley.

Jason 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. Jason is currently based in Washington, DC.