Courtney Shelley is a health data scientist and epidemiologist with 11 years of experience applying rigorous epidemiologic methods to real-world biomedical data and operational disease forecasting. Currently a Lead Associate at Booz Allen Hamilton, she manages teams of modelers and DevOps specialists to deliver weekly disease forecasts and production-ready analytics. Her work blends hands-on data cleaning and feature engineering with modern data engineering practices—version control, medallion architectures, and agile workflows—to make biomedical datasets AI-ready. A former Los Alamos postdoc, she expanded short-term COVID forecasting to hospital and mental-health outcomes and studied misinformation-driven behavior change. Courtney is equally comfortable teaching data hygiene to clinical researchers as she is designing causal ML pipelines, advocating what she calls “full-stack epidemiology.”
11 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Epidemiology, Doctor of Philosophy (Ph.D.), Epidemiology at University of California, Davis
Bachelor of Science (B.S.), Evolution, Behavior, and Ecology, Bachelor of Science (B.S.), Evolution, Behavior, and Ecology at University of California, Los Angeles
Contributions:15 commits, 14 pushes, 1 branch in 1 year 4 months
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