oishika bose

I've analyzed UPI transactions, supply-chain orders, product sales, marketing campaigns, and toy-store data to turn large datasets into stakeholder-ready insights.

Across projects, I've mapped, collected, cleaned, and validated datasets ranging from 80K to 829K+ records. I use SQL, Python with Pandas, Advanced Excel, and Power BI to identify data-quality issues, reconcile discrepancies, define KPIs, and surface trends such as suspicious transactions, late deliveries, pricing effectiveness, and stockout risk.

For a UPI transactions analysis, I validated 250K+ records, defined a 95% success-rate KPI, and built Power BI dashboards to flag suspicious patterns. In marketing campaign analysis, I used Python to model an impressions-to-conversion funnel across 200K records and recommend segment-targeting improvements for ROI.

With an MBA in Marketing Management and a B.Sc. in Information Technology, I bring a business-first lens to analytics. I'm an immediate joiner eager to support cross-functional analytics and BI initiatives.