Senior Data Scientist (Fraud Detection and Investigative Analytics)
Location: Herndon, VA (Remote Work)
Must have an Public Trust Clearance
KEY RESPONSIBILITIES
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Review, maintain, and extend all existing loan fraud indicators developed by TSD, and provide authoritative expertise on analytic method selection.
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Design, develop, test, calibrate, and implement advanced statistical and machine learning models targeting financial fraud, improper payments, and non compliance within SBA programs.
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Build and refine both supervised and unsupervised models, including regression, Bayesian, clustering, and ensemble approaches, and tune candidate models to determine best fit.
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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.
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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.
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Adhere closely to the federal rules of criminal procedure governing protected information, including Rule 6(e).
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Develop case leads for SBA OIG investigations from model outcomes.
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Document all methodology, test models, and production models in a form that satisfies criminal evidentiary requirements.
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Build visualizations and dashboards that convey methodological choices, outcomes, and predictive capability, and iterate them on end user feedback.
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Deliver findings in multiple registers: data summaries and visualizations for investigative staff, executive summaries for OIG leadership.
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Coordinate with the data engineering seat so the architecture supports machine learning efficiently.
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Create programming and automation techniques that improve task efficiency using SharePoint, Python, Excel, Power BI, Power Apps, and similar tools.
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Identify new business questions that expand the scope of analysis and reporting.
Requirements
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.
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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.
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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
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Cloud certification in Azure, AWS, or GCP.
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Direct experience with SBA loan programs, including 7(a), 504, EIDL, or PPP, or with comparable federal lending or grant fraud.
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Entity resolution, record linkage, or graph and network analysis applied to fraud.
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Experience producing analytic products that were used in a criminal referral or prosecution.
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Model explainability practice such as SHAP or comparable feature attribution methods.
Benefits
We are proud to offer competitive compensation and benefits packages to include
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Medical
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Dental
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Vision
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Basic Life
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Health Saving Account
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401K matching
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Three weeks of PTO/Sick
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11 Paid Holidays
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Pre-Approved Online Training
