Summary
Rosie Martinez is a Principal Data Scientist and computational epidemiologist with nine years of experience turning complex health and claims datasets into actionable products and policy insights. She blends rigorous academic training (Sc.D. from Harvard in Molecular Environmental Epidemiology) with hands-on production work—building Databricks pipelines, ML-driven personalization and semantic search, and predictive-denial systems that saved hospitals millions. Rosie has published in top journals and led cross-functional teams at industry leaders (Pfizer, Red Ventures, Olive) while mentoring junior scientists and shaping product direction. She is equally at home teaching advanced analytics—designing curricula and lecturing on CNNs, RNNs, LMMs, and reinforcement learning—and implementing practical solutions like OCR handwriting recognition and contraceptive-distribution forecasting. Notably, she translates domain complexity into usable tools: creating healthcare provider crosswalks, novel patient-level causal features, and knowledge-graph data functions that bridge research and production. Based in Denver, she focuses on maximally impactful data products that influence care delivery and public health decisions.
9 years of coding experience
11 years of employment as a software developer
BS Biochemistry, BS Biochemistry at Seattle Pacific University
Master's Degree Environmental Health Science, Master's Degree Environmental Health Science at Columbia University Mailman School of Public Health
Data Science Immersive Data Science, Data Science Immersive Data Science at Galvanize Inc
Doctorate of Science (Sc.D) Molecular Environmental Epidemiology, Doctorate of Science (Sc.D) Molecular Environmental Epidemiology at Harvard T.H. Chan School of Public Health
Spanish, English