SME customer churn prediction
Scoped churn with BCG’s five-step method, cleaned 30K+ records, engineered price-sensitivity features, and built a Random Forest model with ~75% precision.
I build ML models, real-time data pipelines, and BI dashboards that move from messy records to decisions — with a taste for systems that look sharp and actually ship.
Resume-backed analytics simulations where the important part was not just charts — it was framing business questions and making recommendations.
Scoped churn with BCG’s five-step method, cleaned 30K+ records, engineered price-sensitivity features, and built a Random Forest model with ~75% precision.
Cleaned and transformed ~540K rows, validated quantities/prices, calculated revenue, and created executive visuals for seasonality, markets, and top customers.
Built like systems, not screenshots — forecasting, streaming, automation, monitoring, dashboards.
Inspired by modern component systems: animated background, orbit visual, radar card, bento proof cards, and command-palette style UI — without the ugly Spline embed.
Bachelor of Technology in Artificial Intelligence & Data Science, 2022–2026. Current GPA: 9.73.
I combine business framing, clean data work, ML experimentation, dashboard storytelling, and engineering discipline — useful for entry-level analytics, ML, BI, analytics engineering, and data engineering roles.
I’m looking for Mumbai or remote opportunities where I can build useful analytics products, ML workflows, dashboards, and pipelines.