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About the Role

Apply data science and machine learning to analyze complex financial transaction data for a major federal intelligence and law enforcement bureau. Your analytical models will help identify suspicious patterns, supporting efforts to safeguard the financial system from illicit activity and money laundering.

Responsibilities

• Design, develop, and deploy machine learning models and statistical algorithms to identify complex money laundering techniques within massive financial datasets.
• Perform exploratory data analysis, feature engineering, and model validation using Python, PySpark, and SQL across scalable AWS infrastructure.
• Partner with compliance analysts and federal investigators to translate regulatory requirements into analytical models and visual reports.
• Build maintainable data pipelines, document model logic to agency standards, and lead peer code reviews to ensure reproducible, high-quality data science practices.

Requirements

• 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.
• 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.

Skills

• Python
• PySpark
• SQL
• AWS
• S3
• RDS
• OpenSearch
• R
• Pandas
• Machine Learning
• Statistical Algorithms
• Data Engineering
• Data Analysis
• Feature Engineering
• Model Validation
• Data Pipelines
• Code Review
• Data Dashboards
• Visual Reports

Location

• Washington, DC

Work Type

• On-site
• Full-time

Experience Level

• 4+ years

Education Level

• Bachelor's Degree or higher

About the Company

• A major federal intelligence and law enforcement bureau.