• Developed and deployed an AI-driven training tool for field force managers, transforming extensive feedback textual data into quantifiable insights using Gen AI and LLMs, significantly increasing training effectiveness.• Designed and implemented a full end-to-end data pipeline using MLOps on Databricks for Leqvio (drug), streamlining data processing and model deployment, which improved Healthcare Professionals targeting accuracy by 20%

• Part of the Entresto Driver Analysis project, where I created a machine learning model that generated strategic recommendations, contributing to a $21 million annual revenue increase• Formulated advanced business rules within a ML model to effectively identify physicians most likely to prescribe Entresto, addressing imbalanced datasets, which resulted in a 28% increase in targeting accuracy

• Developed an LSTM-based model that significantly enhanced efficiency, leading to a remarkable 30% reduction in simulation time for Discrete element method (DEM) simulations within blender environments.• Developed and implemented a predictive statistical model with a demonstrated accuracy rate of 85% for estimating tablet sticking effects at production scale.• Designed and deployed a machine learning model that successfully predicted pharmaceutical drug shelf life, achieving a remarkable 83% prediction accuracy rate.• Engineered automation tools utilizing Python to streamline processes, including a web-based application for tracking employee project statuses.