I am an award-winning data science leader with board-certification in informatics and over 20 years experience in healthcare and health data tech. I am passionate about data-driven discovery with impact. I have led numerous enterprise-scale strategic efforts in data science and analytics. I furthered my education at UC Berkeley, Haas School of Business, with an executive certificate in Data Strategy, published the first systematic review of data science models vs. traditional tools predicting a consumer safety risk (with over 30 citations worldwide), and I received the 2019 UCSF Distinguished Dissertation Award.

I am currently serving as enterprise data science manager in the national health plan offices of one the largest health systems in the U.S.; strategic expertise: initiated and led two divisions through development of a 3-year strategic roadmap planning (SWOT, TOWS, RICE) and aligned strategy with business priorities and vision.

My team of data scientists excels at data-driven discovery and delivering business-critical insights on consumer behavior and experience; our work impacts critical strategic deliverables and informs C-level executives at the national level serving 12.6M members across eight U.S. markets.; our analytic capabiliities include development and validation of AI/ML algorithms, prediction of service demands, topic modeling, anomaly detection, consumer segmentation, NLP, and business intelligence services (dashboards and reports). Our projects are large-scale efforts enabled by a high-performance computing infrastructure with an integrated data lake.

Key interests and expertise: Data strategy, AI and machine learning applications, predictive modeling; innovation; business decision support; business strategy; team leadership; digital health and services; econometric evaluations; business case development; quantitative research.