Summary
Thomas Proctor is a data scientist with a Ph.D. in physics and a decade of experience turning complex scientific problems into production-ready data solutions. He combines deep expertise in computational physics, statistical modeling, and scalable data engineering—having built a PostgreSQL database from 150M+ taxi records and scraped/processed ~200GB of public data for credit-worthiness pipelines. His research produced a peer-reviewed breakthrough in random ferromagnet theory (Physical Review Letters) and involved parallelizing algorithms to cut processing time by 15x. Comfortable with low-level code (C, Fortran) and modern tooling (Python, Docker, Selenium), he bridges research rigor with practical deployment. Based in the Bronx, he’s actively seeking roles where mathematical intuition and data engineering meet hard, real-world questions. An uncommon strength is his track record of turning stalled theoretical problems into verifiable, reproducible solutions that scale.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at The Graduate Center, City University of New York
Bachelor of Arts (BA), Physics, Bachelor of Arts (BA), Physics at Reed College
Data Science Intensive, Data Science, Data Science Intensive, Data Science at SlideRule
High School, High School at Greens Farms Academy