Your data already holds the answers — I help you find them.

I design and build custom machine learning models that turn messy business data into clear, actionable predictions. No black boxes. No guesswork. Just models that work.

This isn't a one-size-fits-all deliverable. Complex ML projects need room to breathe — so I structure engagements in phases, so you see real results early and decide how far to go.

Phase 1 — Proof of Concept (1–2 weeks) We validate whether your data can support the model. You get: EDA report, baseline model, first accuracy numbers. → See value before committing to the full build.

Phase 2 — Model Development (2–4 weeks) Feature engineering, model selection, tuning. You get: trained model + performance dashboard (ROC-AUC, F1, precision/recall — not just accuracy).

Phase 3 — Deployment & Integration (1–2 weeks) REST API (FastAPI) on GCP/AWS, ready for your system. You get: live endpoint + documentation + handoff call.

Phase 4 — Ongoing (optional) Model monitoring, retraining, new features. Ideal for teams who want a long-term AI partner — open to retainer or full-time collaboration.

━━ USE CASES ━━ ✦ Credit & loan default risk ✦ Customer churn prediction ✦ Fraud detection ✦ Sales & demand forecasting ✦ Anomaly detection

━━ FEATURED WORK ━━ Credit default prediction system (XGBoost + GCP Cloud Run) — high-precision risk scoring with full feature engineering pipeline.