Summary
Nathaniel Hendrix is a data scientist and researcher with nine years of experience applying epidemiology, natural language processing, and AI to primary care and electronic health records. Currently at the American Board of Family Medicine, he focuses on translating clinical text and EHR data into actionable insights and practical AI implementations for frontline clinicians. His background includes a PhD in Pharmacoeconomics and a PharmD, combining rigorous quantitative methods with domain expertise in pharmacy and health systems. Prior research roles at Harvard T.H. Chan School of Public Health and the University of Washington reflect a strong track record in reproducible, translational health research. Nathaniel is particularly adept at bridging academic rigor and operational deployment—bringing models from paper to clinic workflows. Based in Washington, D.C., he brings a clinician-informed perspective to AI governance and implementation in primary care.
9 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Pharmacoeconomics/Pharmaceutical Economics, Doctor of Philosophy (Ph.D.), Pharmacoeconomics/Pharmaceutical Economics at University of Washington
BA, English (Minor: Anthropology), BA, English (Minor: Anthropology) at Texas State University-San Marcos
Pre-Pharmacy, Pre-Pharmacy at Portland State University