Healthcare Data Analyst

Summary Description: Working directly to support the mission and vision of the CMS, this role conducts thorough evaluations and advanced analyses of potential fraud cases and data inquiries. This will require leveraging claims information and multiple data sources to provide critical support in developing complex, high-value, or sensitive cases that warrant referral to law enforcement, recovery of overpayments, or administrative action; driven by both proactive and reactive data analysis strategies.

Accountabilities: Work with local management, investigators, and analysts to provide reactive and proactive case development support and to fulfill law enforcement data requests Communicate effectively with internal and external customers, including federal law enforcement officers Validate data analysis results and analytically identify potential fraud, waste and/or abuse situations in violation of Medicare/Medicaid laws, guidelines, policies, and regulations Support management requests for CMS reporting requirements Utilize data analysis techniques to detect aberrancies in Medicare/Medicaid claims data and proactively seeks out and develops leads and cases received from a variety of sources including CMS and OIG, fraud alerts, and referrals from government and private sources Work with Statisticians and Data Analysts to provide proactive data analysis results with statistically high probabilities of producing case referrals to law enforcement, overpayments, and/or administrative actions Prepare, develop, and participate in provider, beneficiary, law enforcement, or staff training as related to Medicare fraud, waste and/or abuse data analysis.

Qualifications: Bachelor’s degree in statistics or related discipline with preference given to MA or MS recipients, and/or relevant work experience as a data analyst Minimum 2 years of experience analyzing Medicare and/or Medicaid data. Strong understanding of healthcare claims, ICD-10-CM codes, provider identifiers (NPI), and Medicare/Medicaid billing practices. Minimum 2 years of proven experience in programming with SQL and Python. Hands-on experience with one or more of the following: Pandas, NumPy, Scikit-learn, Seaborn, or Matplotlib. Working knowledge of SAS, Databricks, Snowflake, or Spark. Experience with visualization tools such as Tableau or Power BI.