Arlo Solutions LLC - (765) Data Analyst (Healthcare Fraud)

Remote - USA3w ago

Remote Mid NA Payments Artificial Intelligence Data Analyst Fraud Examiner Python SQL Foundry Power BI Tableau

Requirements

• 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 • 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 • AAP Statement

Responsibilities

• Write, test and document business rules and algorithm logic mapped to FWA schemes. • Support provider risk-scoring and case-prioritization criteria. • Support configuration, code development and deployment on VA's Palantir platform, including data pipelines and system integration. • Help combine claims, enrollment and exclusion data into a single Provider 360 view. • Support anomaly detection and network analysis. • Run the weekly analytics that feed War Room decision packages and the recurring prioritized lead lists. • Extract, clean and analyze federal healthcare data for FWA identification. • Support claim review workpapers. • 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. • Support federal benchmarking and alignment of VHA data analysis with CMS data and methods. • Build dashboards, visualizations and data for quarterly fraud trend and improper payment reduction reports, risk governance reporting and leadership briefings. • Document rule specifications, acceptance criteria and analytic methods. Train VA staff to run War Room analytics on their own.