Summary
Elizabeth Smith is a Data Science Manager with 11 years of quantitative and applied analytics experience, known for turning ultra-large datasets into actionable strategy across customer success, sales, and fisheries science. At KnowBe4 she leads a team of data scientists, architects Snowflake-based ML and conversational analytics solutions, and helped produce IPO-grade TAM estimates used in SEC filings. She pairs deep statistical rigor—from PhD-level fisheries stock assessment and peer-reviewed research—to practical ML ops, deploying retention and cross-sell propensity models that integrate generative AI into account management workflows. A passionate R enthusiast and public speaker, she builds compelling visual narratives for diverse audiences and runs internal R clubs to uplift team capability. Notably, her background spans both ecological modeling and enterprise ML, giving her a rare ability to translate complex scientific methods into scalable business impact.
11 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Master of Science (M.S.), Marine Science, Quantitative Resource Assessment, Doctor of Philosophy (Ph.D.), Master of Science (M.S.), Marine Science, Quantitative Resource Assessment at University of South Florida
Data Science Nanodegree, Data Science Nanodegree at Udacity
Bachelor’s Degree, Biology, Bachelor’s Degree, Biology at Boston University