I am working with the Clearance Analytics team where my responsibilities revolve around quantifying the effectiveness of clearance programs that run every week, and analyzing sales performance to recommend changes in markdown schedules in different item locations. I have earlier worked for the Promo Insights team to carry out in-depth analysis of different offers and promotions across channels, vehicles, pyramids, brands, locations; and quantifying their effectiveness. Prior to that, I worked for Guest Innovation team creating algorithms on customer behavior, identification of transaction patterns in stores and omni-channels and clustering analysis. I have also worked with the Marketing Analytics team on end-to-end propensity model development for different marketing campaigns, and with Healthcare Analytics team where my role involved predictive modeling, guest analytics, insight packets generation using dashboards and provide data-based assistance in manufacturer and insurance negotiation models using sales history. I am currently working on Python, Apache Spark, R and Hive; have extensive knowledge on SAS EG, and have used SAS E-Miner, SPSS and Stata. I completed my Masters degree from Delhi School of Economics with specializations in Macroeconomics, Mathematical Economics, Econometrics and Statistics.