Data Analyst - 176046

Zachary Piper Solutions is seeking a Data Analyst to support the Department of Veterans Affairs’ Veterans Health Administration (VHA) Fraud Rapid Response Center. The role analyzes federal healthcare data, develops fraud-detection rules, identifies suspicious billing patterns, and generates prioritized leads for government review.

Responsibilities:

• Develop, test, and document analytical business rules and algorithm logic designed to identify healthcare fraud, waste, and abuse schemes
• Support provider risk scoring, case prioritization, and fraud detection criteria to help investigators identify high-risk providers and suspicious claims
• Support configuration, code development, deployment, and integration of data pipelines and analytics workflows within VA’s Palantir platform
• Combine claims, enrollment, and provider exclusion data to support a comprehensive Provider 360 view of community care providers
• Perform anomaly detection and network analysis to identify unusual billing patterns, relationships, and potential coordinated fraud schemes
• Execute recurring weekly analytics to generate prioritized lead lists and support War Room decision packages
• Extract, clean, transform, and analyze federal healthcare data to identify potential fraud indicators, improper payments, and overpayments
• Develop and maintain analytical workpapers documenting findings and supporting case review activities
• Back-test fraud detection rules, measure precision and positive predictive value (PPV), analyze false positives, and support quality assurance and corrective action plans
• Support federal benchmarking and align VHA data analysis methods with relevant CMS data and analytical practices
• Build dashboards, visualizations, and analytical outputs for fraud trend reporting, improper payment reduction initiatives, risk governance, and executive briefings
• Document rule specifications, acceptance criteria, data transformations, and analytical methodologies
• Support knowledge transfer and training to help VA staff independently operate and maintain War Room analytics
• Handle protected health information (PHI) and sensitive government data in accordance with HIPAA, VA privacy requirements, and applicable security procedures

Requirements:

• Bachelor's degree in Information Technology, Computer Science, Data Science, Statistics, Health Informatics, or a related field
• 2–5 years of federal healthcare data analytics experience, such as working with Medicare, Medicaid, or VHA data
• Experience developing analytical business rules for healthcare data, fraud detection, payment integrity, or related use cases
• Strong coding skills in SQL and Python, or comparable analytical programming experience with PySpark or R
• Proficiency with analytics platforms and data workflows, including data pipelines, transformations, and dashboards
• Working knowledge of healthcare claims data, including claim types, CPT/HCPCS and ICD-10 codes, National Provider Identifiers (NPIs), provider data, and beneficiary data
• Strong analytical, problem-solving, and documentation skills
• Ability to pass a Tier 2 / Moderate Background Investigation (MBI) and obtain a VA Personal Identity Verification (PIV) card
• Legal eligibility to work in the United States
• Ability to handle PHI and sensitive information in accordance with HIPAA and VA privacy requirements and complete required VA TMS training
• Hands-on experience with Palantir Foundry or Gotham, particularly in healthcare analytics, fraud detection, or payment integrity
• Experience identifying healthcare billing anomalies, including upcoding, unbundling, duplicate billing, impossible days, or billing by excluded providers
• Familiarity with VA Community Care data, the CMS Integrated Data Repository (IDR), the HHS Office of Inspector General's List of Excluded Individuals/Entities (LEIE), or SAM exclusion lists
• Experience with anomaly detection, machine learning, network analysis, or link analysis
• Experience back-testing analytical rules, measuring positive predictive value (PPV), and evaluating false-positive rates
• Proficiency with Power BI, Tableau, or similar data visualization and reporting tools
• Certified Fraud Examiner (CFE) credential or a relevant data analytics certification