Summary
Timothy Heath is a machine learning engineer with 13 years of experience building production ML systems and data pipelines, currently applying his expertise at Spotify. He blends deep academic training—a PhD in Mathematics and a BS in Mathematics & Statistics—with practical engineering leadership from roles at eBay where he led teams improving search ranking and personalized recommendations. Comfortable across Scala, Python, Java, distributed compute and low-latency caches, he moves models from research to real-time, contextualized results. A five-time hackathon winner and open-source enthusiast, he brings a pragmatic, metrics-driven approach to designing scalable algorithms and pipelines. Based in New York, he pairs strong technical mentorship with a proven track record of shipping impactful, product-facing ML features.
13 years of coding experience
5 years of employment as a software developer
Bachelor of Science (BS), Mathematics and Statistics, 3.951, Bachelor of Science (BS), Mathematics and Statistics, 3.951 at University of Michigan
Doctor of Philosophy (PhD), Mathematics, 4.0, Doctor of Philosophy (PhD), Mathematics, 4.0 at Columbia University in the City of New York
English