Summary
Jerome Dixon is a senior operations research analyst and data engineer with a decade of experience blending cloud-native AWS engineering, advanced ML, and logistics/healthcare operations to deliver production-ready analytics and decision support. He has architected event-driven data lakes, real-time streaming pipelines, and serverless MLOps that power everything from pediatric heart transplant risk calculators to multi-tenant VR surgical skill assessment. A former Navy Supply Corps officer and logistics director, he brings rare operational rigor to analytics—turning complex supply-chain and clinical questions into idempotent, auditable workflows and explainable AI. Jerome’s toolkit spans Step Functions, Lambda, DynamoDB, QuickSight, SHAP/FFA, and ensemble survival models, and he frequently bridges research and product to push prototypes into live inference APIs. Based in Richmond, VA, he is passionate about aligning people, process, and technology to increase organizational effectiveness in high-stakes domains.
10 years of coding experience
7 years of employment as a software developer
M.S., IT Management, M.S., IT Management at Naval Postgraduate School
Master of Decision Analytics (M.D.A.) with Healthcare Concentration, Data Science, Master of Decision Analytics (M.D.A.) with Healthcare Concentration, Data Science at Virginia Commonwealth University
Lean Six Sigma Black Belt, Industrial Engineering, Lean Six Sigma Black Belt, Industrial Engineering at Villanova University
Center of Excellence in Logistics & Technology (LOGTECH), Center of Excellence in Logistics & Technology (LOGTECH) at UNC Kenan-Flagler Business School
B.S., General Engineering, B.S., General Engineering at United States Naval Academy
English