In this role, you will 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. This work would be performed on-site in Washington, DC.
Key Responsibilities:- Financial Crime Pattern Detection: Designing, developing, and deploying machine learning models and statistical algorithms to identify complex money laundering techniques—such as structuring, layering, and smurfing—within massive financial datasets.
- Cloud-Native Data Engineering & Analysis: Performing exploratory data analysis, feature engineering, and model validation using Python, PySpark, and SQL across scalable AWS infrastructure, including S3, RDS, and OpenSearch.
- Stakeholder Collaboration & Translation: Partnering directly with compliance analysts and federal investigators to translate complex regulatory requirements into high-impact analytical models and clear visual reports.
- Model Integrity & Workflow Standardization: Building maintainable data pipelines, document model logic to agency standards, and lead peer code reviews to ensure reproducible, high-quality data science practices.
- 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 Required
- Active Top Secret SCI clearance
- Bachelor's degree or higher in a related field
- 4+ years data science experience building, validating, and deploying ML models using Python and/or R
- Hands-on experience analyzing Bank Secrecy Act (BSA) or Anti-Money Laundering (AML) transaction data
- Hands-on experience executing queries and managing data pipelines within AWS (S3, RDS/PostgreSQL, OpenSearch, Lambda)
- Strong proficiency with SQL and big-data frameworks (e.g., PySpark, Pandas) for large-scale data analysis
- Experience building intuitive dashboards and visual reports for non-technical operational teams
- Experience establishing automated model documentation and reproducible pipelines in regulated environments
What We Do
Elevate your business with Omniscius, where cutting-edge Business Intelligence meets exceptional Talent Acquisition. We specialize in empowering teams with custom training, offering strategic staffing solutions, and crafting unique talent acquisition strategies. Our focus on Federal Contracting and a robust partner ecosystem ensures your business stays ahead in government contracting and recruitment. Let us optimize your talent acquisition with our expertise and turn your challenges into opportunities. Discover the Omniscius advantage and transform your business landscape today
