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nashcastillo/README.md

👋 Nashely Castillo

Criminologue & AML/CFT Compliance Officer based in Paris — currently learning Python and Machine Learning to apply data science to financial crime detection.

🇫🇷 Criminologue & Responsable conformité LCB-FT, en formation Data Essentials chez Jedha Bootcamp.

🎯 Focus

  • 🕵️ Anti-Money Laundering (AML/CFT) — suspicious activity detection, typology analysis
  • 📊 Data analysis applied to financial crime — Python, pandas, scikit-learn
  • ⚖️ 11+ years in banking compliance (Western Union, ING, La Banque Postale, CITI)

🚀 Featured project

aml-detection-saml-d — Machine Learning pipeline to flag suspicious transactions on the SAML-D dataset (800k transactions, 0.1% imbalance). Decision Tree retained with 43% recall.

🛠️ Tools

Python pandas scikit-learn Jupyter Excel SQL (basics) Git · domain: LCB-FT KYC/KYB EDD Sanctions screening

📫 Get in touch

Open to opportunities in AML/Compliance roles bridging regulation and data.

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  1. aml-detection-saml-d aml-detection-saml-d Public

    Decision Tree model achieving 43% recall on suspicious transaction detection — SAML-D dataset (800k tx, 0.1% imbalance)

    Jupyter Notebook