(765) Data Analyst (Healthcare Fraud)

Arlo Solutions; United States; Hybride; USD 90 000 - 130 000; Plein temps

Résumé du poste

Arlo Solutions is supporting VA's War Room as a Data Analyst (Healthcare Fraud). The role analyzes claims, enrollment and exclusion data using Palantir, builds rules to detect fraud, and surfaces prioritized leads for government review.

The position is remote with on-site requirements and requires Public Trust clearance. Responsibilities include developing FWA detection rules, provider risk-scoring support, platform development on Palantir, anomaly detection, weekly analytic runs, data

Qualifications

• Experience analyzing federal healthcare data for FWA identification.
• Experience with Palantir analytics platform preferred.
• Ability to write and test business rules for fraud detection.

Responsabilités

• Write, test and document rules for detecting fraud, waste and abuse.
• Support analytics for Provider 360 view and anomaly detection.
• Run weekly analytics feeds for War Room decision packages.
• Extract, clean and analyze health data related to FWA.
• Back-test rules and support QA and corrective action plans.
• Benchmark VHA data analysis with CMS data and methods.

Connaissances

Data analysis

Problem solving

Attention to detail

Outils

Palantir

Description du poste

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.

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