Jay Li

Master's

Data Science

Statistics

Intrado

Data scientist

• Working on healthcare AI projects using state-of-the-art methods to enhance prediction of high cost claimants, determining the impact of engagement program with Health Advocate, and the accuracy of clinical risk stratification. • Predicted with 85% accuracy the future year’s high-cost, high-risk claimants by XGBoost model with spatial, temporal and spike features based on the 1.4M data: member demographics, costs, clinical procedures and diagnoses. • Analyzing member-level variation using statistical methods to quantify cost impact from engagement with care management services provided by Health Advocate