Data Science and AI leader with 9+ years of experience across healthcare, pharmacy, retail, and enterprise environments, specializing in analytics strategy, predictive modeling, patient engagement, geospatial analytics, retail intelligence, and AI-driven decision systems. Proven ability to lead cross-functional analytics initiatives, translate complex data into executive-ready insights, and build scalable AI and healthcare analytics solutions using Python, SQL, R, Snowflake, Databricks, NLP, LLMs, and cloud-based ML platforms.
Lead data science, analytics, and AI initiatives across healthcare, pharmacy, retail, and enterprise clients. Design predictive analytics and AI-driven engagement solutions, manage cross-functional initiatives, and lead development of healthcare analytics platforms. Also worked as an AI/ML consultant for CVS Health on retail analytics and operational intelligence solutions.
Partnered with senior leadership on digital transformation and applied AI initiatives across clinical healthcare, pharmacy analytics, patient engagement, and enterprise data science programs. Designed scalable analytics workflows and multimodal data integration pipelines using Snowflake and Databricks, and led geospatial analytics-driven patient outreach systems.
Led analytical research and model evaluation initiatives focused on machine learning deployment efficiency, operational scalability, enterprise AI performance, and production readiness. Developed an ML toolkit for model recommendation and contributed to an AutoDL platform with pre-deployment SLA analysis.
Developed predictive recommendation systems and personalization models supporting targeted marketing, customer engagement, audience segmentation, and campaign optimization. Built analytics-driven email recommendation systems and worked extensively with AWS technologies and distributed ML deployment environments.
Created NLP and analytics algorithms to process customer feedback and improve customer satisfaction. Led a team of two ML engineers on churn analysis and prediction, mentored interns, and collaborated with data warehouse and engineering teams on production analytics workflows.
Master of Science, Data Science
Bachelor of Science, Computer Science
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