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SENIOR DATA SCIENTIST (FRAUD DETECTION AND INVESTIGATIVE ANALYTICS)

Node.Digital
Full-timesenior

Job description

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. We are proud to offer competitive compensation and benefits packages to include • Medical • Dental • Vision • Basic Life • Health Saving Account • 401K matching • Three weeks of PTO/Sick • 11 Paid Holidays • Pre-Approved Online Training

Skills

PythonPandasSQLSQL ServerPostgreSQLAzureAWSGCPPower BIPower AppsSharePointRegressionClassificationBayesianClusteringEnsembleNatural Language ProcessingEntity ResolutionRecord LinkageGraph AnalysisNetwork AnalysisSHAPModel Explainability