Lead the company's effort on utilizing text analytics and machine learning for the next generation Hub/PAP and Remote Sales platform to provide substantive insights into customer communications and automatically create tailored strategy and next best action.

Predict patient drop off probability in th next 3 months based on patient enrollment infomation and behavior history using machine learning approach. 

Worked on price sensitivity analysis to offer optimal pricing strategy based on the specific price sensitivity relation for each client segment to increase the bottom line for about $20M every year.

Used Predictive Modeling techniques and complicated data attributes including patient insurance records (inpatients, outpatients, diagnosis, procedures …), physician medical claims, Rx to describe the patient and physician behavior patterns, and more importantly to identify the behavior drivers for using specific products to provide comprehensive actionable insights. This led to the first successful direct to patient campaign launch through pharmacies.