Senior Data Scientist (Fraud Detection and Investigative Analytics)

Senior Data Scientist (Fraud Detection and Investigative Analytics)

Location: Herndon, VA (Remote Work)

Must have an Public Trust Clearance

KEY RESPONSIBILITIES

• Review, maintain, and extend all existing loan fraud indicators developed by TSD, and provide authoritative expertise on analytic method selection.
• Design, develop, test, calibrate, and implement advanced statistical and machine learning models targeting financial fraud, improper payments, and non compliance within SBA programs.
• Build and refine both supervised and unsupervised models, including regression, Bayesian, clustering, and ensemble approaches, and tune candidate models to determine best fit.
• Perform data quality analysis on source tables to identify abnormalities and inconsistencies, and develop repeatable processes for combining and analyzing large relational, structured, and unstructured sources.
• Collaborate directly with criminal investigators to determine and execute analytic strategies supporting loan fraud cases, adapting analysis as case needs shift and proactively surfacing data quality issues.
• Adhere closely to the federal rules of criminal procedure governing protected information, including Rule 6(e).
• Develop case leads for SBA OIG investigations from model outcomes.
• Document all methodology, test models, and production models in a form that satisfies criminal evidentiary requirements.
• Build visualizations and dashboards that convey methodological choices, outcomes, and predictive capability, and iterate them on end user feedback.
• Deliver findings in multiple registers: data summaries and visualizations for investigative staff, executive summaries for OIG leadership.
• Coordinate with the data engineering seat so the architecture supports machine learning efficiently.
• Create programming and automation techniques that improve task efficiency using SharePoint, Python, Excel, Power BI, Power Apps, and similar tools.
• Identify new business questions that expand the scope of analysis and reporting.

Required:

Education

Master's, Ph.D., or doctorate level equivalent degree in data science, machine learning, computer science, mathematics, or a related field. Alternatively, ten years of applied work experience in any of the same fields.

• 5+ years Designing, implementing, and maintaining advanced AI systems and predictive models, including both supervised and unsupervised models.
• 5+ years Developing analytic rules and models using leading edge analytic tools and best practices.
• 5+ years Developing regression, classification, and other statistical models to identify anomalies, patterns, and predictive variables.
• 3+ years Providing data support for criminal investigations into financial fraud or abuse of government funds.
• 3+ years Manipulating data in Python. Pandas is required.
• 3+ years Working in a modern cloud environment: Azure, AWS, or GCP. Certifications preferred.
• 2+ years Conducting advanced data analysis in SQL, specifically SQL Server and PostgreSQL.
• 2+ years Developing and scaling natural language processing solutions.
• 2+ years Presenting methods and findings to technical and non technical stakeholders, both orally and in written products and visualizations.

PREFERRED QUALIFICATIONS

• Cloud certification in Azure, AWS, or GCP.
• Direct experience with SBA loan programs, including 7(a), 504, EIDL, or PPP, or with comparable federal lending or grant fraud.
• Entity resolution, record linkage, or graph and network analysis applied to fraud.
• Experience producing analytic products that were used in a criminal referral or prosecution.
• Model explainability practice such as SHAP or comparable feature attribution methods.