(765) Data Analyst (Healthcare Fraud)

Position Description:

Arlo Solutions is supporting the Department of Veterans Affairs (VA) Veterans Health Administration (VHA) Office of Integrity and Compliance (OIC) in standing up and running the VHA Fraud Rapid Response Center ("VA War Room"). The War Room protects Veterans and taxpayer dollars through data analytics, fraud risk assessment and fast administrative action, in line with Executive Orders 14395 and 14243. The Data Analyst (Healthcare Fraud) is Essential Personnel on the fraud, waste and abuse (FWA) analytics team.

Working under the Analytics and Technology Program Director and the Senior Data Analyst, this person uses VA's Palantir analytics and workflow platform to analyze VHA claims, enrollment and exclusion data. The analyst builds and tests business rules that detect potential fraud and overpayments, and surfaces anomalies and prioritized leads for OIC review. This includes supporting the Provider 360 view of community care providers, anomaly detection and network analysis to find coordinated billing schemes.

The role is advisory and analytical. All final decisions stay with Government personnel.

Location: Remote with On-Site Requirements

Clearance: Public Trust

Responsibilities and/or Success Factors:

• FWA Rule & Algorithm Development:
• Write, test and document business rules and algorithm logic mapped to FWA schemes.
• Support provider risk-scoring and case-prioritization criteria.
• Platform Development:
• Support configuration, code development and deployment on VA's Palantir platform, including data pipelines and system integration.
• Provider 360 & Anomaly Detection:
• Help combine claims, enrollment and exclusion data into a single Provider 360 view.
• Support anomaly detection and network analysis.
• Weekly Analytic Runs:
• Run the weekly analytics that feed War Room decision packages and the recurring prioritized lead lists.
• Data Extraction & Analysis:
• Extract, clean and analyze federal healthcare data for FWA identification.
• Support claim review workpapers.
• Quality Assurance & Back-Testing:
• Back-test rules, track rule precision and support QA and corrective action plans.
• The QASP targets at least 65% positive predictive value in month one and 70% by Day 60.
• Benchmarking:
• Support federal benchmarking and alignment of VHA data analysis with CMS data and methods.
• Dashboards & Reporting:
• Build dashboards, visualizations and data for quarterly fraud trend and improper payment reduction reports, risk governance reporting and leadership briefings.
• Documentation & Knowledge Transfer:
• Document rule specifications, acceptance criteria and analytic methods. Train VA staff to run War Room analytics on their own.

Minimum Qualifications Including Certificates:

• Must be legally eligible to work in the United States
• Able to pass a Tier 2 / Moderate Background Investigation (MBI) and get a VA PIV card
• Bachelor's degree in information technology, Computer Science or a related field (such as data science, statistics or health informatics)
• 2-5 years of federal healthcare data analytics experience, such as with Medicare, Medicaid or VHA data Experience writing healthcare data analytics business rules
• Strong coding skills in SQL and Python (or PySpark/R)
• Proficiency with analytics platforms, including data pipelines, transformations and dashboards
• Working knowledge of healthcare claims data, such as claim types, CPT/HCPCS and ICD-10 codes, NPIs and provider and beneficiary data
• Able to handle PHI and sensitive information under HIPAA and VA privacy requirements, and to complete the required VA TMS trainings

Desired Qualifications:

• Hands-on experience with Palantir Foundry or Gotham Healthcare FWA or payment integrity analytics experience, such as detecting upcoding, unbundling, duplicate billing, impossible days or excluded providers
• Experience with VA Community Care data, the CMS Integrated Data Repository (IDR), or the OIG LEIE and SAM exclusion lists Anomaly detection, machine learning or network/link analysis experience
• Rule back-testing and precision measurement experience (PPV, false-positive analysis)
• Experience with Power BI, Tableau or similar visualization tools
• Certified Fraud Examiner (CFE) or a data or analytics certification