Summary
Clinton Brownley is a Lead Data Scientist with 11 years of experience translating complex data into strategic decisions across tech and academia, currently leading analytics at Tala while lecturing graduate courses at UC Berkeley and other universities. He blends rigorous causal inference, econometrics, and machine learning with practical product and people analytics experience from roles at Meta, WhatsApp, and Facebook. Clinton is skilled in R, Python, and JavaScript and has contributed course-aligned Python analytics materials—demonstrating hands-on expertise in data cleaning, Excel/CSV workflows, and Pandas-based transformations. His work spans forecasting, simulation, and multi-objective decision analysis, enabling him to communicate insights that shape business and policy. Notably, he pairs industry practice with a Ph.D.-level grounding in public administration and policy, bringing discipline in causal thinking to product and policy problems. Based in Saratoga, CA, he combines startup founding experience with large-scale platform analytics to drive measurable impact.
11 years of coding experience
11 years of employment as a software developer
Ph.D. Public Administration and Policy, Ph.D. Public Administration and Policy at American University
M.S. Public Policy and Management, M.S. Public Policy and Management at Carnegie Mellon University - Heinz College of Information Systems and Public Policy
B.S. Ethics History and Public Policy; Policy and Management, B.S. Ethics History and Public Policy; Policy and Management at Carnegie Mellon University