At Eli Lilly, I build commercial and Medical Affairs analytics products that turn fragmented healthcare data into decision-ready insights. I unified eight sources into Activity+, a certified Databricks data product used by 200+ BI&A users.
I build statistical and machine-learning products for healthcare decision-making, including patient journey analysis, engagement prediction, HCO prioritisation, and NLP- and LLM-based disease-state classification. My work has eliminated manual effort, reduced a medical activity pipeline from an hour to seconds, and supported care-gap detection across 30+ disease states.
I bring an M.Sc. in Data Science and a biostatistics foundation, with hands-on experience across Python, SQL, Databricks, Power BI, and interpretable modelling. I also developed neuroimaging classification models, urban bus ETA prediction pipelines, and statistical analyses for clinical research.
