Senior Data Scientist – Machine Learning

General Dynamics Information Technology

Senior Data Scientist building supervised machine learning models for GDIT’s multi-payer healthcare fraud analytics program. Deploying explainable, evidence-backed models for investigators and stakeholders.

Posted 8/15/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $123,250 - $166,750 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Expertise in designing, training, and validating supervised machine learning models, particularly in the healthcare domain, with a strong focus on feature engineering, model deployment, and effective communication of analytic outcomes to diverse stakeholders.

Highest-signal resume keywords

Supervised Machine Learning Model DevelopmentPython ProficiencySQL ProficiencyHealthcare Claims Data ExperienceFeature Engineering

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Supervised Machine LearningFeature EngineeringModel ValidationModel DeploymentData AnalysisEntity ResolutionImbalanced Data HandlingOut-of-Time EvaluationLeakage DetectionPrecision-Focused Metrics

Soft Skills

CommunicationCollaborationAnalytical ThinkingProblem SolvingStakeholder Engagement

Certifications & Qualifications

Public Trust Clearance

Industry Keywords

Healthcare ClaimsMedicareMedicaidICD-10CPTHCPCSDRGFraud DetectionWaste ManagementAbuse Risk

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Design, train, and validate supervised machine learning models scoring providers and billing patterns for fraud, waste, and abuse risk
Use investigative case-level data, payer feedback, and public exclusion and enforcement data as labels
Perform entity resolution linking enforcement records to providers in claims
Design validation for delayed labels, limited coverage, extreme class imbalance, and rapidly shifting schemes
Engineer features against billions of claims within the data warehouse using Python and SQL
Deliver ranked model outputs with human-readable rationales and claim-level evidence
Adjust scores for case mix and specialty and optimize precision at the top of review queues
Deploy models into production, including scheduling, versioning, and drift monitoring
Establish modeling and deployment practices for the Data Science team
Collaborate with FWA Subject Matter Experts to distinguish genuine anomalies from policy- or edit-explained patterns
Communicate methodology and limitations to HFPP partners and stakeholders
Support investigators and clients in adopting and acting on analytic output

Requirements

What you’ll need

Master's in a quantitative field, or Bachelor's with equivalent hands-on experience
5+ years building, validating, and delivering supervised machine learning models on real-world data
Experience with incomplete, delayed, or biased labels
Experience deploying and maintaining production models, including scheduling, versioning, and drift monitoring
Python and SQL proficiency
Feature engineering within very large-scale data warehouses
2+ years working with healthcare claims data, including Medicare, Medicaid, or commercial claims
Knowledge of coding systems such as ICD-10, CPT, HCPCS, and DRG
Experience designing validation for imbalanced and temporally shifting problems
Knowledge of out-of-time evaluation, leakage detection, calibration, and precision-focused ranked-output metrics
Ability to explain model output to non-technical investigators
Ability to defend methodology to technical audiences and present analytic outcomes to clients and stakeholders
Must be able to obtain/maintain Public Trust
No work visa sponsorship provided
Candidates must reside in the United States

Benefits

Comp & perks

Medical plan options, including plans with Health Savings Accounts
Dental plan options
Vision plan
401(k) plan with pre-tax and post-tax contributions and company match
Full flex work weeks where possible
Vacation, sick and personal time
Paid holidays
Paid parental leave
Military leave
Bereavement leave
Jury duty leave
Typically 15 days of paid leave per calendar year
Additional 10 paid holidays per year
Up to 160 hours of paid family leave in a rolling 12-month period for eligible employees
Short- and long-term disability benefits
Life insurance
Accidental death and dismemberment insurance
Personal accident insurance
Critical illness insurance
Business travel and accident insurance
Remote work