As a data specialist, I worked on parameters to improve the statistical forecast using triple exponential smoothing, and allocation of the flagging process to generate the right amount of forecast based on the type of the customer. Perform anomaly detection using Python to find the outliers in time series and remove them to make the base forecast more accurate

Used SQL window functions, CTEs, and stored procedures to create reports and use them to manage KPI dashboards and purchasing scorecards. Performed Recency, Frequency & Monetary (RFM) segmentation in Python on customers to identify which products are core competencies and which products the business needs to invest more to achieve sales targets. • Created an ARIMA, Holt-Winters, and ETS statistical forecasting model using R programming and MS Excel for more than 6,000 SKUs