- Current POS Retailers support- New POS Retailers onboarding- Conducting change requests for existing retailers- Master Data Support- DQ Anomalies Checking- Restatements for historical periods- User Trainings/Education

-Analysis of current process for promo forecasting-Negotiation of the requirement of key process holders for the project-Creation logic for promo forecasting in future tool-Creation of local BI Tool, which calculates sell in forecast for a client. Tool was created fully with Python and data aggregation from Cloud Azure Services with SQL and PySpark, being in status of P&G One Data Team member according with best practices of team.-Result analysis, root-cause split, creation of hypothesis for improvement

-Creating accurate forecasts in cooperation with S&Op departments -Providing analysis in a specific section of the business by sku, brands and customer. -Modeling material flows within the client: the level of filling of stocks, sell-out, sell-in. -Research of promotional activities in order to increase the accuracy of forecasting -Using ERP systems and statistical package for time series forecasting (JDA, SPSS)