Data Analyst

Zachary Piper Solutions is seeking a Data Analyst (Healthcare Fraud) to support the DVA VHA’s Fraud Rapid Response Center. The role analyzes federal healthcare data, develops fraud detection rules, identifies suspicious billing patterns, and generates prioritized leads using VA’s Palantir analytics platform.

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
• 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