Data Analyst - 176046

Zachary Piper Solutions; United States; Teletrabalho; USD 100 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Medical, Dental, Vision

401(k) Plan

Holidays and PTO

Remote work within continental US

Resumo da oferta

Zachary Piper Solutions seeks a Data Analyst (Healthcare Fraud) to support VA VHA Fraud Rapid Response Center. You will analyze federal healthcare data, develop fraud detection rules, and generate prioritized leads for government review, using Palantir analytics.

The role emphasizes collaboration with the analytics War Room, rule back-testing, dashboards, and HIPAA compliance, with 100% remote work within the continental United States.

Qualificações

• Bachelor’s degree in IT, CS, Data Science, Statistics, Health Informatics, or related field.
• 2–5 years of federal healthcare data analytics experience with Medicare/Medicaid or VHA data.
• Experience developing analytical rules for healthcare data, fraud detection, or payment integrity.
• Strong coding skills in SQL and Python, or PySpark and/or R.
• Familiarity with Palantir Foundry or Gotham and analytics dashboards.

Responsabilidades

• Develop, test, and document analytical rules and algorithm logic to identify FWA.
• Support provider risk scoring, case prioritization, and fraud detection criteria.
• Configure, code, deploy, and integrate data pipelines and analytics workflows in VA’s Palantir platform.
• Combine claims, enrollment, and provider data for a Provider 360 view.
• Perform anomaly detection and network analysis to flag unusual billing patterns.
• Execute weekly analytics to generate prioritized leads for review.
• Extract, clean, transform, and analyze federal healthcare data for indicators of fraud.
• Document findings in analytical workpapers and support case reviews.
• Back-test rules, measure PPV, analyze false positives, and support QA actions.
• Support HIPAA compliance and VA privacy requirements and TMS training.
• Build dashboards and visualizations for fraud trend reporting and executive briefings.

Conhecimentos

SQL

Python

PySpark

R

Analytical

Documentation

Problem-solving

Formação académica

Bachelor’s degree in IT/CS/Data Science/Statistics/Health Informatics

Ferramentas

Palantir Foundry

Palantir Gotham

Power BI

Tableau

Data pipelines

Descrição da oferta de emprego

Zachary Piper Solutions is seeking a Data Analyst (Healthcare Fraud) to support the DVA VHA in establishing and operating a high-visibility Fraud Rapid Response Center. This mission-driven initiative focuses on accelerating the detection of healthcare fraud, waste, and abuse (FWA) to protect Veterans and safeguard taxpayer dollars. The Data Analyst will support the War Room’s analytics team by analyzing federal healthcare data, developing fraud detection rules, identifying suspicious billing patterns, and generating prioritized leads for government review. This role offers hands‑on experience supporting a high‑profile federal healthcare initiative using VA’s Palantir analytics platform.

Responsibilities of the Data Analyst (Healthcare Fraud) include:

• 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.

Qualifications of the Data Analyst (Healthcare Fraud) include:

• 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.

Desired Qualifications:

• 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.

Compensation for the Data Analyst (Healthcare Fraud) includes:

• Salary Range: $100,000–$110,000 depending on experience
• Benefits: Medical, Dental, Vision, 401(k) Plan, Holidays, PTO, and sick leave as required by law
• Work Arrangement: 100% remote within the continental United States, with East Coast working hours & occasional travel to DC, for in‑person meetings

Keywords:

Data Analyst, Healthcare Fraud, Healthcare Data Analytics, Fraud Waste and Abuse, FWA, Fraud Detection, Payment Integrity, Improper Payments, Federal Healthcare, VA, VHA, CMS, Medicare, Medicaid, VA Community Care, Palantir Foundry, Palantir Gotham, SQL, Python, PySpark, R, Data Pipelines, Data Transformation, Business Rules, Algorithm Development, Provider Risk Scoring, Provider 360, Anomaly Detection, Network Analysis, Link Analysis, Healthcare Claims, CPT, HCPCS, ICD-10, NPI, Beneficiary Data, CMS Integrated Data Repository, IDR, LEIE, SAM Exclusion Lists, Rule Back-Testing, Positive Predictive Value, PPV, False-Positive Analysis, Power BI, Tableau, Public Trust, Tier 2 MBI, VA PIV.