Data Scientist
On-siteWashington, District of Columbia, United States or Washington, United States
Job Summary
Design and deploy machine learning models to detect complex money laundering techniques within massive financial datasets. Perform exploratory data analysis and feature engineering using Python, PySpark, and SQL across scalable AWS infrastructure. Partner with compliance analysts and federal investigators to translate regulatory requirements into high-impact analytical models and visual reports. Build maintainable data pipelines, document model logic to agency standards, and lead peer code reviews to ensure reproducible practices. This on-site role in Washington, DC requires a Top Secret SCI clearance and 4+ years of data science experience analyzing Bank Secrecy Act transaction data.
Required Qualifications
- Active Top Secret SCI clearance
- Bachelor's Degree or higher in a related field from an accredited college or university
- 4+ years of dedicated data science experience building, validating, and deploying machine learning models using Python and/or R
- Hands-on experience analyzing Bank Secrecy Act (BSA) or Anti-Money Laundering (AML) transaction data to detect illicit financial patterns
- Hands-on experience executing queries and managing data pipelines within AWS cloud environments (e.g., S3, RDS/PostgreSQL, OpenSearch, Lambda)
- Strong proficiency with SQL and big-data frameworks (e.g., PySpark, Pandas) to analyze large-scale structured and unstructured datasets
Desired Qualifications
- Experience building intuitive data dashboards and clear visual reports to present findings to non-technical operational teams
- Demonstrated track record of establishing automated model documentation and reproducible data pipelines in a regulated environment
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