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Senior Data Scientist (Fraud Detection and Investigative Analytics)

Node.Digital

Washington, DCRemoteJobNo compensation foundTracked 3w agoSeen in employer's feed 3 days ago

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At a glance

Compensation
No compensation found
Location
Washington, DCRemote
Work Authorization
Not specified

Requirements

Credentials this posting asks for.

Public Trust clearanceMaster's degree

Job overview

Node.Digital is hiring a Senior Data Scientist (Fraud Detection and Investigative Analytics). Senior Data Scientist role focused on fraud detection and investigative analytics for SBA loan programs, requiring public trust clearance, advanced statistical and machine learning model development, data quality analysis, collaboration with investigators, and creation of visualizations and dashboards to support criminal investigations.

Key focus areas include Review, maintain, and extend all existing loan fraud indicators and provide expertise on analytic method selection, Design, develop, test, calibrate, and implement advanced statistical and machine learning models for financial fraud, and Build and refine supervised and unsupervised models including regression, Bayesian, clustering, and ensemble approaches.

Important skills include SharePoint, Python, Excel, Power BI, Power Apps, and Pandas. Preferred (not required): Azure, AWS, GCP, and SHAP.

Skills & qualifications

RequiredNice to have

Skills

SharePointPythonExcelPower BIPower AppsPandasMicrosoft SQL ServerPostgreSQLAnalytic Method SelectionStatistical ModelingMachine Learning ModelsSupervised ModelsUnsupervised ModelsRegressionBayesianClusteringEnsemble ApproachesData Quality AnalysisCombining Large Relational SourcesAnalyzing Large Relational SourcesCombining Structured SourcesAnalyzing Structured SourcesCombining Unstructured SourcesAnalyzing Unstructured SourcesAnalytic StrategiesModel Outcomes DocumentationProduction Models DocumentationBuilding VisualizationsBuilding DashboardsProgrammingAutomation TechniquesNLPCollaborationPresenting Methods to Technical StakeholdersPresenting Findings to Technical StakeholdersFinancial Fraud DetectionImproper Payments DetectionNon Compliance DetectionAzureAWSGCPSHAPModel Explainability PracticeFeature Attribution MethodsSBA Programs7(a) Loan Program504 Loan ProgramEIDL Loan ProgramPPP Loan ProgramFederal Lending Fraud

Qualifications

Public Trust ClearanceMaster's in Data ScienceMaster's in Machine LearningMaster's in Computer ScienceMaster's in MathematicsMaster's in Related FieldPh.D. In Data SciencePh.D. In Machine LearningPh.D. In Computer SciencePh.D. In MathematicsPh.D. In Related FieldDoctorate Level Equivalent Degree in Data Science

Benefits

Medical Insurance
Dental Insurance
401(k) Match
Paid Time Off

Full 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.

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.

  • 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.

Benefits

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

You've read the whole posting — now see how you match it.

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