Senior Data Scientist (Fraud Detection and Investigative Analytics)

Location: Herndon, VA (Remote Work)Must have an Public Trust ClearanceKey ResponsibilitiesReview, maintain, and extend all existing loan fraud indicators developed by TSD, and provide authoritative expertise on analytic method selectionDesign, develop, test, calibrate, and implement advanced statistical and machine learning models targeting financial fraud, improper payments, and non compliance within SBA programsBuild and refine both supervised and unsupervised models, including regression, Bayesian, clustering, and ensemble approaches, and tune candidate models to determine best fitPerform data quality analysis on source tables to identify abnormalities and inconsistencies, and develop repeatable processes for combining and analyzing large relational, structured, and unstructured sourcesCollaborate 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 issuesAdhere closely to the federal rules of criminal procedure governing protected information, including Rule 6(e)Develop case leads for SBA OIG investigations from model outcomesDocument all methodology, test models, and production models in a form that satisfies criminal evidentiary requirementsBuild visualizations and dashboards that convey methodological choices, outcomes, and predictive capability, and iterate them on end user feedbackDeliver findings in multiple registers: data summaries and visualizations for investigative staff, executive summaries for OIG leadershipCoordinate with the data engineering seat so the architecture supports machine learning efficientlyCreate programming and automation techniques that improve task efficiency using SharePoint, Python, Excel, Power BI, Power Apps, and similar toolsIdentify new business questions that expand the scope of analysis and reportingRequirementsRequired:EducationMaster'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 practices5+ 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 QualificationsCloud certification in Azure, AWS, or GCPDirect experience with SBA loan programs, including 7(a), 504, EIDL, or PPP, or with comparable federal lending or grant fraudEntity resolution, record linkage, or graph and network analysis applied to fraudExperience producing analytic products that were used in a criminal referral or prosecutionModel explainability practice such as SHAP or comparable feature attribution methodsBenefitsWe are proud to offer competitive compensation and benefits packages to includeMedical DentalVisionBasic Life Health Saving Account401K matchingThree weeks of PTO/Sick11 Paid HolidaysPre-Approved Online Training