Summary
Eliot Brenner is an AI research scientist in New York with 12 years of experience applying deep learning and NLP to high-impact domains such as finance, legal, and industrial inspection. At Goldman Sachs he builds conversational QA, document summarization, and signal-extraction systems from unstructured text, drawing on prior roles scaling ML for search and recommendation at Walmart Labs and Shutterstock. He combines a rigorous academic foundation—a PhD in Mathematics from Yale and postdoctoral experience in number theory—with hands-on product deployments, including leading data science at a startup acquired by LMI Technologies. Eliot’s profile reflects a rare blend of theoretical depth and production engineering, enabling him to turn foundational models into practical tools for domain experts.
12 years of coding experience
8 years of employment as a software developer
Mathematics, Mathematics at University of California, Berkeley
BS, BA, BA, Mathematics, Chemistry, Philosophy, BS, BA, BA, Mathematics, Chemistry, Philosophy at Virginia Tech
PhD, Mathematics, PhD, Mathematics at Yale University
Master of Science (M.S.), Scientific Computing, Master of Science (M.S.), Scientific Computing at NYU