Sid Feygin is a Senior Engineering Manager and seasoned data scientist with 12 years of experience building ML-driven platforms for transportation and mobility systems, now leading the data platform team for commercial software and services at General Motors. He combines deep academic training (PhD and MS from UC Berkeley) with hands-on engineering across startups and giants—designing large-scale simulation, privacy-preserving data pipelines, and inverse reinforcement learning models used to analyze commuter behavior. His work spans production-grade Spark/TensorFlow pipelines, travel demand microsimulation, and research published from industry projects such as Uber’s BISTRO. Known for translating complex research into scalable products, he’s delivered systems that process city-scale movement data and enabled differentially private synthetic traces for real-world use. Based in San Francisco, he blends rigorous experimentation with product-minded leadership to drive high-impact ML and data systems in transportation.
12 years of coding experience
6 years of employment as a software developer
Ph.D Civil Engineering, Ph.D Civil Engineering at UC Berkeley College of Engineering
BS Environmental Engineering, BS Environmental Engineering at Columbia Engineering
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Sid Feygin - Senior Engineering Manager at General Motors