CVS Health delivers millions of offers to over 80 million customers and patients on a daily basis to improve the customer experience and put patients on a path to better health. In 2018, CVS Health embarked on a journey to personalize the customer and patient experience through machine learning on a Microsoft Azure Databricks platform. This presentation will discuss how the Microsoft Azure Databricks environment enabled rapid in-market deployment of the first machine learning model within six months on billions of transactions using Apache Spark. It will also discuss several use cases for how this has driven and delivered immediate value for the business, including test and learn experimentation for how to best personalize content to customers. The presentation will also cover lessons learned on the journey in the evolving industries of cloud computing and machine learning in a dynamic healthcare environment.
Michelle Un is a Director of Data Engineering at CVS Health. Michelle is currently focused on the productionalization and deployment of machine learning models to personalize and improve the patient experience for CVS™ retail pharmacy customers. Previously, Michelle supported CVS pharmacy's compliance analytics workstreams, including outlier detection and visualization, and has also worked in the public policy and non-profit sector, always with a passion for using data to answer challenging problems.
Raghu Nakka leads the Front Store Data Engineering team at CVS Health and is responsible for building and maintaining the Front Store Personalization Engine. His big data journey with CVS Health began in 2013 where he initially built the big data frame work for PBM Book of Business and Finance applications and later as a lead big data architect for Front store personalization. Before CVS Health Raghu worked as a consultant working with Finance and Healthcare companies.