Summary
Matt Richfield is a Senior Data Scientist and technical leader with 12 years of experience building production-ready ML systems across startups, enterprise, and academia. He combines deep quantitative training (PhD in Chemical & Biomolecular Engineering) with hands-on engineering—authoring internal Python libraries, Streamlit/Docker prototypes, and Poetry-based deployment templates to standardize model production. At companies from Microsoft and Getty Images to Shelf Engine and Glue he’s led cross-functional teams, launched greenfield recommendation and causal models, and delivered millions in savings via controlled experiments. He also teaches data analytics at Northeastern, bridging industry practice and pedagogy, and has a track record of scaling testing and CI/CD practices (400+ unit tests) to dramatically reduce production incidents. Notably comfortable moving between biology-scale data projects and business-facing forecasting, he’s as fluent in SQL/Postgres and Pandera checks as he is in mentoring and roadmapping for long-term data strategy.
12 years of coding experience
11 years of employment as a software developer
Bachelor of Science (B.S.) Chemical Engineering, Bachelor of Science (B.S.) Chemical Engineering at University of California, Berkeley
PhD Chemical and Biomolecular Engineering, PhD Chemical and Biomolecular Engineering at University of Illinois Urbana-Champaign
English