End-to-end fintech analytics case study analyzing user behavior, churn, transaction trends, and pricing strategy using Power BI.

Advanced SQL analytics project demonstrating CTE layering, window functions, percentile modeling, and structured data transformations.

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.

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

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.

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.