(765) Data Analyst (Healthcare Fraud)

Role overview

This data analyst role supports a federal healthcare fraud, waste, and abuse (FWA) analytics program that protects beneficiaries and public funds through rapid, evidence-based data analysis. The position sits on an analytics team that builds and operates detection rules, risk scoring, and anomaly detection to surface prioritized leads for reviewer action. The work is advisory and analytical in nature, with all final decisions reserved for government personnel.

Responsibilities

- Develop, test, and document business rules and algorithm logic mapped to FWA schemes, including provider risk-scoring and case-prioritization criteria. - Support configuration, code development, data pipelines, and system integration on an enterprise analytics and workflow platform. - Combine claims, enrollment, and exclusion data into a unified provider view, and apply anomaly detection and network analysis to surface coordinated billing patterns. - Execute recurring weekly analytics runs that feed decision packages and prioritized lead lists for leadership review. - Extract, clean, and analyze federal healthcare data, producing claim-review workpapers and supporting quality assurance efforts. - Back-test rules, track precision metrics, and support corrective action plans aimed at program performance targets. - Build dashboards and visualizations for quarterly fraud trend reports, improper payment reduction reports, and briefings for senior stakeholders. - Document rule specifications, acceptance criteria, and analytic methods, and train program staff to run analytics independently.

Requirements

- Eligibility to work in the United States and ability to pass a Tier 2/Moderate Background Investigation and obtain a federal PIV card. - Bachelor's degree in information technology, computer science, data science, statistics, health informatics, or a closely related field. - 2-5 years of federal healthcare data analytics experience with Medicare, Medicaid, or comparable programs. - Demonstrated experience writing healthcare data analytics business rules. - Strong coding skills in SQL and Python (or PySpark/R). - Working knowledge of healthcare claims data, including CPT/HCPCS and ICD-10 codes, NPIs, and provider and beneficiary data. - Ability to handle protected health information under HIPAA and federal privacy requirements, including completion of required privacy trainings.

Nice to have

- Hands-on experience with Palantir Foundry or Gotham, or payment integrity analytics detecting upcoding, unbundling, duplicate billing, impossible days, or excluded providers. - Familiarity with community care data, the CMS Integrated Data Repository, or federal exclusion databases such as the OIG LEIE and SAM lists. - Anomaly detection, machine learning, or network and link analysis experience. - Rule back-testing and precision measurement experience, including positive predictive value and false-positive analysis. - Experience with Power BI, Tableau, or comparable visualization tools. - Certified Fraud Examiner (CFE) or a relevant data or analytics certification.

Benefits and work setup

- Remote position with periodic on-site requirements. - Public Trust clearance.