Mohammad Kaif

I’m a B.Tech CSE (AI & ML) fresher who turns raw data into business insights through SQL, Python, interactive dashboards, and ML-backed analytics. Across 4 end-to-end portfolio projects, I’ve worked with datasets of 100K+ records to build KPI reporting, EDA, and production-ready logic.

I built a full “India Startup Funding Intelligence” platform that unifies 3,215 records (2015–2024) using a custom Python ETL pipeline (scraper → cleaner → SQLite loader). I deployed a FastAPI REST API with 6 endpoints and OpenAPI/Swagger, and trained an XGBoost model achieving 77.29% accuracy—supported by a Streamlit dashboard for trends and live funding predictions.

I also developed analytics systems for real-world decisions, including a logistics & supply chain platform (30,000 shipments) where XGBoost reached 85.6% recall for delay prediction, plus multi-page Streamlit dashboards for monitoring and cost analysis. To connect insights to action, I delivered a global job market dashboard (Power BI) and an e-commerce SQL analysis (100,000+ orders) that identified one-time buyers (96.88%) as a retention risk and linked churn findings to repeat-purchase campaign recommendations.