Jesse Cahill is a Senior Data Scientist in New York with eight years of experience turning large, messy datasets into actionable product insights and robust, reusable data pipelines. He blends strong production-minded Python engineering—modular code, AWS S3 migrations, and scalable ETL—with applied ML for content and product teams, most recently at Hinge after roles at Peloton and M Science. His background in epidemiology and bioengineering gives him a unique lens for causal thinking and experimental design, informing how he frames the “so what” of analyses for stakeholders. Known for automating repeatable workflows (including name-matching and regex-driven categorization) and cutting query times via database re-architecture, he prioritizes both clear storytelling and operational efficiency.
8 years of coding experience
9 years of employment as a software developer
Master of Science - MS, Data Science, Master of Science - MS, Data Science at Columbia University in the City of New York
Bachelor's Degree, Bioengineering, Bachelor's Degree, Bioengineering at State University of New York at Binghamton
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