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🛡️ Architecting data infrastructure
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🛡️ Architecting data infrastructure
  • Joined Apr 28, 2026

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anuj-data-lab/README.md

🔬 Anuj Data Lab

Data Engineering | Mathematical Auditing | Automated Extraction

Welcome to the Lab. I build resilient data infrastructure for businesses that require high-integrity market intelligence. I do not just scrape data; I extract, audit, and structure it for enterprise deployment.

⚙️ The Arsenal

  • OVERSEER_V2: A statistical anomaly detection engine using Z-score mathematics to audit datasets for market intelligence and risk management.
  • MERCENARY_V1: A stealth web scraping engine engineered with Python and Selenium to bypass modern bot protections.
  • IRONCLAD_ETL: (In Development - Enterprise Database Pipeline)

🛠️ Technical Stack

  • Languages: Python, SQL
  • Data Processing: Pandas, NumPy
  • Extraction: Selenium, BeautifulSoup
  • Infrastructure: SQLite, Relational Database Modeling

Pinned Loading

  1. AEGIS_V1 AEGIS_V1 Public

    AEGIS_V1: An automated Model Risk Management engine using Kolmogorov-Smirnov statistical tests to detect data drift in production AI systems.

    Python

  2. OVERSEER_v2 OVERSEER_v2 Public

    OVERSEER_V2: A Python-based statistical anomaly detection engine using Z-score analysis to audit large datasets for market intelligence and risk management.

    Python

  3. IRONCLAD_ETL IRONCLAD_ETL Public

    IRONCLAD_ETL: A robust Python-based data pipeline designed to extract messy web data, validate integrity with custom logic, and load structured payloads into secure SQL databases.

    Python

  4. MERCENARY_V1 MERCENARY_V1 Public

    MERCENARY_V1: A stealth web scraping and automated data extraction engine engineered with Python and Selenium to bypass modern bot protections.

    Python