M.Sc. Data Science (Northeastern) · M.Sc. Information Technology · B.Sc. Accounting. 5+ years building fintech and logistics systems. I turn messy operational data into auditable pipelines, transparent models, and decisions someone can defend.
Traceable data first. Intelligence second.
| Project | What it does | Stack |
|---|---|---|
| forensic-healthcare-billing-screen | Peer-group anomaly screening for healthcare billing. Hierarchical peer fallback, services-weighted benchmarks, robust z-scores, composite screening score. 18 passing tests. | Python · pandas · Excel |
| Executive-Sales-Dashboard | Executive sales dashboard with KPI traceability and pivot-table evidence. | Excel · pivot analysis |
| amazon-financial-sql-analytics (in progress) | SQL analytical model for Amazon financials with executive dashboard. | SQLite · SQL · Excel |
Notebook-based exploratory and modeling work — migration from Colab in progress.
Fraud detection project in development.
| Project | What it does | Stack |
|---|---|---|
| reconciliation-engine | O(n) transaction reconciliation engine for fintech. Hash-map matching, five-status classification, value-at-risk reporting, FastAPI service. 10 passing tests. | Python · FastAPI · pytest |
- 🔍 LLM explanation layer on top of the reconciliation engine — traceable data first, intelligence second
- 📊 Migrating analytics projects to SQL
- 📓 Migrating data science notebooks to GitHub