Project Overview:

• Performed end-to-end data analysis and ETL processes using PySpark, Python, and SQL on Azure Databricks, handling 40MM transaction data from multiple databases, presented key customer insights on Tableau

• Implemented RFM model for customer segmentation, formulated promotion campaign strategy, and designed A/B tests for the loyalty program

• Built ML model to forecast customer attrition period with 95.4% accuracy & 91.7% F1 score, developed CatBoost regression model accurately predict days until next purchase within a range of ±1.69 days