Affinity-based consumer segmentation analysis linking product attributes to distinct customer personas, with strategic implications for pricing, positioning, and portfolio design.

Cleaned and analyzed real-world public transit delay data using Python (pandas, NumPy) with Matplotlib/Seaborn visualizations to uncover temporal and route-level reliability patterns.

End-to-end HR MIS reporting project using PostgreSQL and Excel. Covers dimensional modeling, SQL-based KPI validation, Excel Power Query & Power Pivot modeling, KPI reconciliation, and automated A4 MIS report generation with validation controls, closely reflecting real-world HR MIS workflows.

A customer attrition risk tool built with SQL and Power BI. The project transforms raw banking data into a weighted scorecard to identify high-risk customers, surfacing a Critical segment with a 90% churn rate, a 4.4x lift over the ~20% baseline. Outputs an actionable Hit List to enable proactive, data-driven retention strategies.