Summary
Mark Vandergon is an Expert Lead Data Scientist at the Federal Reserve Bank of New York with a decade of experience applying advanced analytics, AI/ML, and NLP to inform policy, markets, and financial stability. He advises senior leaders on data strategy and capability development while leading cross-functional teams to translate research prototypes into production analytics and operating models. His background spans research labs (neuroscience and urban science), fintech and healthtech consulting, and hands-on product analytics, giving him an unusual blend of policy-facing rigor and product-minded engineering. Co-author of a working paper using text analysis to study Fed transparency, he has deep domain experience across Markets, Research & Statistics, and Supervision within the Federal Reserve System. Based in New York, he pairs academic training in computational analysis and public policy with practical experience building data platforms and supervisory analytics.
10 years of coding experience
6 years of employment as a software developer
B.S.B. Finance, B.S.B. Finance at University of Minnesota - Carlson School of Management
Master of Science in Computational Analysis & Public Policy Computer Science and Public Policy, Master of Science in Computational Analysis & Public Policy Computer Science and Public Policy at University of Chicago