Summary
Jeffrey Doker is a Senior Data Scientist with a PhD in Mathematics and over a decade of hands-on experience building production machine learning systems for high‑impact consumer platforms. He has led recommendation and logging initiatives at Spotify that measurably increased content consumption, and architected Kickstarter’s first recommendation stack that helped drive millions in monthly pledges. Comfortable across research and engineering, he ships end-to-end pipelines in cloud and containerized environments, mentors peers, and translates technical work into product strategy. A former quantitative engineer in sports analytics, he brings a knack for turning mathematical insight into practical, revenue‑driving features. Based in Amherst, MA, he describes himself as a mathematician-engineer and creator, blending rigorous theory with pragmatic delivery.
11 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (PhD), Mathematics, Doctor of Philosophy (PhD), Mathematics at UC Berkeley
Bachelor of Science (BS), Mathematics, Bachelor of Science (BS), Mathematics at University of Florida