Senior Data Scientist – Fraud Detection, Investigative Analytics

Node.Digital

Senior Data Scientist focusing on fraud detection and investigative analytics for the U.S. government.

Posted 7/30/2026full-timeRemote • District of Columbia, Washington • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and implementing advanced statistical and machine learning models for financial fraud detection, with a strong focus on data quality analysis and collaboration with investigative teams. Proficient in programming and automation techniques to enhance task efficiency and deliver actionable insights through visualizations and dashboards.

Highest-signal resume keywords

Machine Learning Model DevelopmentData Quality AnalysisPython Programming (Pandas)Cloud Environment Experience (Azure, AWS, GCP)Statistical Modeling (Regression, Classification)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingMachine LearningData AnalysisNatural Language ProcessingSQL (SQL Server, PostgreSQL)Data VisualizationAnalytic Method SelectionModel CalibrationData ManipulationPredictive Analytics

Soft Skills

CollaborationCommunicationProblem-SolvingAdaptabilityAttention to Detail

Tools & Technologies

PythonPower BIPower AppsSharePointAzureAWSGCPExcelPandasSQL

Industry Keywords

Financial FraudGovernment FundsCriminal InvestigationsData ScienceAnalytic Tools

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPandasPostgresPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Medical
Dental
Vision
Basic Life
Health Saving Account
401K matching
Three weeks of PTO/Sick
11 Paid Holidays
Pre-Approved Online Training