Summary
William Wyatt is a Senior Data Scientist in Los Angeles with 11 years of experience building scalable data systems and applied ML for high-impact domains ranging from energy forecasting to criminal justice. He blends deep quantitative training (PhD work in mathematics and economics, BS in physics) with hands-on engineering—designing geocoding/GIS pipelines, parallelized processing that cut compute from six months to three weeks, and web apps and crawlers that power large-scale analyses. His research explores how large language models reason, decide, and take risks, and he has customized GPT-like systems for legal and retail applications that produced real-world policy and product changes. Comfortable across signal processing, statistical causal inference, and production ML, he’s as likely to be found optimizing Redis-backed recovery and SVM/AdaBoost ensembles as prototyping a web frontend from his GitHub habit of “can’t stop making web apps.”
11 years of coding experience
3 years of employment as a software developer
AS Mathmatics Computational Physics, AS Mathmatics Computational Physics at College of Marin
Doctor of Philosophy - PhD Mathematics and Economics, Doctor of Philosophy - PhD Mathematics and Economics at Claremont Graduate University
University of California Santa Cruz