Architecting automated extraction engines and mathematical anomaly detection pipelines for enterprise intelligence.
I don't just move data — I build systems that extract, audit, and structure it with precision. Currently focused on enterprise-grade data infrastructure, statistical risk modeling, and stealth extraction pipelines.
| Project | Description |
|---|---|
| AEGIS_V1 | Model Risk Management engine using Kolmogorov-Smirnov tests to detect data drift in production AI systems |
| OVERSEER_V2 | Statistical anomaly detection using Z-score analysis for market intelligence and risk auditing |
| IRONCLAD_ETL | Robust ETL pipeline — extracts messy web data, validates integrity, loads into secure SQL databases |
| MERCENARY_V1 | Stealth web scraping engine built with Python & Selenium to bypass modern bot protections |
Languages: Python, SQL
Data & Math: Pandas, NumPy, Z-score analysis, Kolmogorov-Smirnov tests
Extraction: Selenium, BeautifulSoup
Infrastructure: SQLite, Relational Database Modeling, ETL Pipelines
IRONCLAD_ETL— hardening the pipeline for enterprise deployment- Expanding statistical auditing capabilities across live datasets
- Building backend APIs with FastAPI and SQLite
Precision over speed. Integrity over volume.