[All remote jobs](https://jobicy.com/jobs.md)[![Arlo Solutions logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/0a3b43a1-221.jpeg)](https://jobicy.com/company/arlo-solutions.md)[Arlo Solutions](https://jobicy.com/company/arlo-solutions.md) # (765) Data Analyst (Healthcare Fraud) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/arlo-solutions.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUndisclosedDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceDirectorPublished20 Oct 2026Apply before19 Nov 2026Listing views59Application actions4Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Arlo Solutions seeks a Data Analyst to support the VA Veterans Health Administration Fraud Rapid Response Center. The role analyzes claims, enrollment, provider, and exclusion data to identify healthcare fraud, waste, abuse, and potential overpayments. Responsibilities include developing and back-testing detection rules, supporting Palantir data pipelines, performing anomaly and network analysis, and producing dashboards and leadership reports. The analyst will work with sensitive federal healthcare data and contribute to Provider 360 views, prioritized investigative leads, and knowledge transfer to VA staff. Strong SQL, Python, healthcare claims knowledge, and eligibility for a VA background investigation are essential. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 3/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a technically demanding analytics role involving regulated healthcare data, fraud-detection logic, Palantir platform work, and measurable rule-precision targets. The analyst must translate complex fraud patterns into reliable, documented analytical rules while supporting recurring operational deliverables. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$97,500US market range (per year)$85k–$115k0$126.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary was disclosed. The yearly cadence and USD market estimate are inferred from the full-time US federal healthcare data analyst context, required technical skills, security eligibility, and 2–5 years of relevant experience. ## Core skills Skills and capabilities most closely associated with this opportunity. [SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[Healthcare claims analysis](https://jobicy.com/jobs?search_keywords=Healthcare%20claims%20analysis.md)[Fraud detection](https://jobicy.com/jobs?search_keywords=Fraud%20detection.md)[Business rule development](https://jobicy.com/jobs?search_keywords=Business%20rule%20development.md)[Palantir Foundry](https://jobicy.com/jobs?search_keywords=Palantir%20Foundry.md)[Data pipelines](https://jobicy.com/jobs?search_keywords=Data%20pipelines.md)[Anomaly detection](https://jobicy.com/jobs?search_keywords=Anomaly%20detection.md)[Network analysis](https://jobicy.com/jobs?search_keywords=Network%20analysis.md)[Provider risk scoring](https://jobicy.com/jobs?search_keywords=Provider%20risk%20scoring.md)[Data visualization](https://jobicy.com/jobs?search_keywords=Data%20visualization.md)[Power BI](https://jobicy.com/jobs?search_keywords=Power%20BI.md)[Healthcare coding systems](https://jobicy.com/jobs?search_keywords=Healthcare%20coding%20systems.md)[HIPAA compliance](https://jobicy.com/jobs?search_keywords=HIPAA%20compliance.md)[Quality assurance](https://jobicy.com/jobs?search_keywords=Quality%20assurance.md) Sample interview questionsHow would you design a rule to detect potentially duplicate healthcare billing claims?I would first define a duplicate-claim pattern using fields such as patient identifier, provider NPI, service date, CPT/HCPCS code, modifier, billed amount, and claim status. I would use SQL or Python to identify exact and near-duplicate combinations, account for legitimate corrected or adjusted claims, and document exclusions. Finally, I would back-test the rule against reviewed cases, measure precision and false positives, and refine thresholds before deployment. What healthcare claims data elements are most important when investigating potential upcoding? Key elements include CPT/HCPCS codes, ICD-10 diagnosis codes, place of service, provider specialty and NPI, units billed, service date, beneficiary characteristics, and reimbursement amount. I would compare coding distributions against peer providers with similar specialties and patient populations. Material deviations would be evaluated alongside clinical and billing context before being prioritized for review. How would you measure whether a fraud-detection rule is performing effectively? I would measure positive predictive value, false-positive rate, lead volume, recovery or prevented-payment potential, and consistency across provider groups or time periods. I would use adjudicated or investigator-reviewed outcomes as the validation set and monitor performance after deployment. A rule should be adjusted or retired when it produces excessive low-value leads or its precision declines. Describe how you would use network analysis to identify coordinated billing schemes. I would model providers, beneficiaries, facilities, addresses, bank or ownership indicators where available, and claims as connected entities. I would look for unusual shared relationships, tightly connected clusters, repeated referral patterns, synchronized billing behavior, and outlier utilization. Findings would be scored and paired with supporting claim-level evidence for investigator review rather than treated as final determinations. How do you protect PHI while developing dashboards and analytical outputs? I apply least-privilege access, use approved VA systems and secure storage, and limit outputs to the minimum necessary information. I avoid exposing direct identifiers in broad dashboards, apply role-based access controls, and follow HIPAA and agency-specific privacy procedures. I also document data handling, validate sharing permissions, and promptly report any suspected privacy issue through the required process. Opportunity details ## About this role. Company Summary Arlo Solutions (Arlo) is an information technology consulting services company that specializes in delivering technology solutions. Our reputation reflects the high quality of the talented Arlo Solutions team and the consultants working in partnership with our customers. Our mission is to understand and meet the needs of both our customers and consultants by delivering quality, value-added solutions. Our solutions are designed and managed to not only reduce costs, but to improve business processes, accelerate response time, improve services to end-users, and give our customers a competitive edge, now and into the future. 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 AAP Statement We are proud to be an Affirmative Action and Equal Opportunity Employer and as such, we evaluate qualified candidates in full consideration without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, national origin, age, disability status, protected veteran status, and any other protected status. Show more [Apply now >](https://jobicy.com/jobs/156082-765-data-analyst-healthcare-fraud.md) > Annual salary information is not provided for this position. 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