Research and Data science analytics professional with 7 years of experience in building statistical, econometric, Machine learning and Time series forecasting models, which includes areas of Retail and Healthcare and customer analytics solutions.My core objective is "Making sense of Data" and expertise in converting complex business problems into mathematical/statistical equations and solve the problems using advanced methods and converting back into business solutions. Responsibilities:- Problem Identification and Data collection- Data understanding and data preparation- Model building and delivering insightsAnalytical solutions provided:- Merchandising and Replenishment planning.- Demand Forecasting.- Customer 360 - Customer propensity, Customer lifetime value, Recommendations (cross-sell and up-sell), Customer segmentation and Customer churn (contractual and non-contractual settings).- Multi-tenant forecasting.- Day-part and Product affinity analytics.- geospatial analysis- Healthcare predictive Analysis- Fraud Analytics on Retail bills