Remote Sr. Healthcare Data Analyst (Full-time, Remote)

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Description:

  • The Senior Healthcare Data Analyst at Integrity Management Services is responsible for maintaining confidentiality and security of sensitive information related to healthcare systems.
  • They build models and conduct analytics to contribute to Medicare and Medicaid fraud detection efforts.
  • The analyst identifies anomalies in healthcare data to detect fraud, waste, and abuse.
  • Using tools like Python, R, SQL, and SAS, they manipulate and extract Medicare, Medicaid, and other healthcare claims data.
  • The role involves continuous learning of Medicare and Medicaid policy changes and evaluating their impact on fraud detection models.
  • The analyst provides subject matter expertise to other analysts, participates in testing sprints and projects, and communicates effectively with technical and non-technical users.
  • They lead team projects, stay informed about industry changes, and exercise discretion in company policies and practices.

Requirements:

  • Minimum 4-year degree in statistics, mathematics, computer science, or related field OR minimum of 6 years of data analysis experience in the healthcare industry.
  • 6 years of professional experience working with large and complex data sets.
  • Minimum of 3 years of data analysis experience in the healthcare industry.
  • Advanced knowledge of analytic, mathematical, and statistical methods.
  • Experience with Medicare and Medicaid claims, ICD10 codes, HCPCS, DRG.
  • Proficiency in tools like SAS, SQL, Python, R, Databricks, and Microsoft Office products.
  • Ability to respond to tasks in a cooperative and timely manner, adapt to change, and work collaboratively in a team.
  • Must be able to pass a public trust background check.

Benefits:

  • Opportunity to work remotely.
  • Competitive salary and benefits package.
  • Opportunity for professional development and growth.
  • Collaborative and supportive work environment.
  • Opportunity to work on projects that make a difference in fraud detection in government programs.
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