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Sr. Fraud, Waste, and Abuse Data Analyst

1 month ago
United States
Full-time
Senior
Data Analyst
Data Science and Analytics
Feature Engineering Generative AI Machine Learning Python R SQL
Apply Now
HHAeXchange

HHAeXchange

HHAeXchange is a premier homecare management software connecting providers, payers, and caregivers for proactive care, efficiency, and transparency in the industry.

Health Care Providers & Services
251-1K
Founded 2008
View All Jobs 18

Description

  • Analyze Medicaid claims, visit, EVV, and billing datasets to identify suspicious patterns such as visit overlaps, impossible service combinations, duplicate/inflated billing, billing spikes, upcoding, and beneficiary identity issues.
  • Develop, refine, and scale detection queries and analytical logic to automate identification of fraud, waste, and abuse across large datasets.
  • Apply and test AI/ML techniques (anomaly detection, predictive risk scoring, clustering) and collaborate with data science on feature engineering, model validation, and operationalization.
  • Leverage generative AI/LLM tools to accelerate investigation summarization, pattern narrative development, and analytical workflows.
  • Contextualize anomalies using end-to-end revenue cycle knowledge (claims submission, adjudication, remittance, denials/appeals) to assess integrity implications.
  • Translate analytical findings into clear product and engineering requirements; contribute to the design of dashboards, alerting systems, and investigation workflows.
  • Serve as a subject matter expert on FWA and program integrity, advising product teams and payer/state stakeholders on clinically and operationally sound detection logic.
  • Present findings and recommendations to internal stakeholders and payer clients (state Medicaid agencies and MCOs); document methodologies to support compliance, audit readiness, and regulatory reporting.
  • Support proactive research to identify emerging fraud patterns and continuously test, validate, and improve detection models and tools.

Requirements

  • 5–7 years experience in healthcare analytics, payment integrity, fraud detection, program integrity, forensic data analysis, or a related field.
  • Strong SQL proficiency with demonstrated ability to query and analyze large, complex healthcare datasets.
  • Experience identifying patterns, anomalies, or outliers in healthcare claims or billing datasets and applying revenue cycle context (claims submission, adjudication, EOB/835, denials/appeals).
  • Working knowledge of Medicaid billing structures and artifacts, including HCPCS/CPT codes, claim types (837P/837I), and home- and community-based services billing rules.
  • Familiarity with federal Medicaid program integrity regulations (e.g., 42 CFR Parts 431, 447, 455) and CMS oversight/reporting expectations.
  • Experience using AI or machine learning tools for anomaly detection, risk scoring, or predictive analytics and collaborating with data science teams on model development and feature engineering.
  • Working knowledge of provider operations in home care or personal care settings and how MCOs and state Medicaid agencies operate and oversee provider networks.
  • Preferred: experience with payment integrity organizations, managed care plans, or state Medicaid agencies; experience with Python, R, or advanced analytics/visualization tools; familiarity with EVV data and 21st Century Cures Act mandates.
  • Preferred: familiarity with Medicaid audit processes (RAC/UPIC/MIC), CARC/RARC codes, claim edit logic, prior authorization workflows, exposure to generative AI/LLM tools, or professional certifications such as CFE, AHFI, CPC, or CHC.

Benefits

  • Base salary range $130,000–$155,000 per year (does not include variable compensation).
  • Benefits-eligible position with competitive health plan options.
  • Paid time off and company-paid holidays.
  • 401(k) retirement program with a Company-elected match.
  • Fully remote role for U.S.-based candidates located in EST or CST time zones.
  • Opportunity for travel up to 10% and participation in other company-sponsored programs.

Interested in this position?

Apply directly on the company website

Apply Now

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