Parikshit Girikala

Retail Product Analytics || Promotions

• Perform Lift Analysis for different products to show the effectiveness of promotions.
  Deployed GLM & GBM models to predict the sales of products at productxstorexdate level.
• Then classify the promotion into different categories depending upon the performance and other metrics.

Consumer Analytics || UK Retailer

• Provide end to end support on analytics & decision making on different promotional events targeting sales growth & market share.
• Automate the general briefs to improve the efficiency of turn around time with accurate outputs.
• As part of automation created a python script to read the data from snowflake, complete the required data wrangling & analysis, create an automated PPT using python PPTX with required tables & charts with all the formatting.

FC Level Capacity Chatter

• Plan and Perform capacity actions for various fulfillment centers by coordinating with the ground ops and track the impact of capacity action on different metrics like SLA, Utilization etc.
• Built a Power BI dashboard to track various metrics at multiple levels during the event period

Fleet Return Sensing

• Performed an extensive Data exploratory Analysis which helped us to find out the important factors contributing to vehicle return.
• Further performed time series analysis and build an ensemble model comprising of (ARIMA,ARIMAX, Prophet, Hierarchical Time Series, GAM) and created Power BI report which helped our clients to predict the vehicle return time, place, quantity.

Analytics Dashboard | Incentives

• Leveraged historical sales data to perform distribution analysis and show case the top tactics driving the maximum sales
• Created a Power BI dashboard with various views by utilizing the learnings from the analyses This helped the clients understand the complexity associated with stacking of multiple incentives and enabled proactive decision making

COVID – 19 Mitigation plans for short term Forecasts

• Predicting the expected demand in a short run at a weekly level for essential and non-essential products
• Providing directional insights into expected recovery time (from COVID – 19) for different operating regions using SIRD model
• Applied regression models considering external regressor like Active cases, recovered cases and death rate to predict short term demand

Analytics Dashboard | Cluster Analysis On Countries

• Leveraged John Hopkins covid data to perform cluster analysis to understand the behavior of different countries towards pandemic
• Created a Power BI dashboard with various views by utilizing the learnings from the analyses