• Responsible for leading the Data Analytics team and Supporting the Customer Loyalty Program for entire North America Region• Devise and implement Customer Science and Automation work such as Customer Segmentations, Personalization, ChurnPrevention, Fraud Detection, Customer Lifetime Value into the Loyalty Analytics ecosystem• Working closely with the Business Loyalty Managers and leading the Loyalty Analytics team to do data analysis and provide fact based actionable insights into CRM Communications (all direct marketing efforts including e-mail, SMS, push notifications)• Lead ad-hoc analytical support to business stakeholders to achieve key business objectives using test and control analytics, dashboard analytics, benchmarking, statistical concepts, and financial measures to guide decision making• Facilitate best practice sharing and contribute to automation and improvement of existing processes

->Responsible for setting up a new team and aiding business partners by formulating the Analytical Framework for Analyses->Evaluated weather Impact analysis to estimate impact on sales $ & traffic for affected regions, identified by WDD score->Directed bucket analysis to modify promo $ impact for promotions related to “Buy more & Save more” based on ticket size->Led pre-post analysis to assess impact on demand, sales & margin due to moving from instore inventory to Regional Distribution Centers for Heavy Appliances->Managed product line review based on sales penetration, Margin % to enhance localization space->Assessed basket and attachment analysis to gauge high performing add-ons and promotional strategies

->Directed feature development projects with the app developers. Supervised and mentored a team of 4 Product Analysts and help grow the analytics team stronger->Developed a Demand Projection Model for planning a sustainable growth resulted in 3X growth in a year by doing 2 million orders per month and reducing the Loss per Transaction from -65 INR per order to -32 INR->Built Demand-Supply Mismatch (DSM) Model to revamp and structure three sides of the platform (demand, supply & merchant availability) to optimize money burn, user and delivery partner experience on platform->Optimized burn per order and to get incremental orders in terms of offer discounting, customer micro-segments were created by using RFM. For these segments A/B experiments were designed to identify optimal discounting range for each group

->Led and managed a team of 3 Business Analysts. Engaged with the Clients, understood their requirements and fulfilled them to their utmost satisfaction->Devised a Logistic model to identify significant drivers affecting NPS score of a customer to prioritize areas for improvement and simulated % change in NPS by improving key drivers->Estimated impact on business after launch of check-in app and doing a phased rollout in different markets->Measured impact of store remodeling & new initiatives (such as banning on Plastics) on customer experience and store sales

->Designed a model to predict drivers and intervene to improve customer satisfaction by analyzing customer journey with help of techniques like audio mining, sentimental analysis, and classification techniques

->Designed statistical models to understand untapped needs in market utilizing ANCOVA, Chi-square test etc.->Proved safety profile of client’s drugs using statistical hypothesis testers like Kaplan-Meier Survival Analysis and Log-Rank Test, helps in getting approvals across globe