Senior Healthcare Data Analyst - Fraud Detection & Analytics

Description

In this role, you will play a crucial part in enhancing healthcare systems through in-depth data analysis and collaboration. Leveraging your intermediate computer and software skills, you will help achieve business goals focused on delivering high-quality results for clients. The ideal candidate thrives both independently and as part of a team, working alongside Statistical and Data Analysts to provide essential analytical support.

Key Responsibilities

• Maintain strict confidentiality and security of all sensitive and business-related information accessed during your work.
• Follow privacy and security protocols to protect sensitive information, ensuring compliance with all relevant policies and procedures.
• Complete all required privacy and security training, both on an annual basis and as needed, to meet compliance standards.
• Build models and conduct analytics to combat Medicare and Medicaid fraud, waste, and abuse, identifying potential fraud patterns and validating these through rigorous testing.
• Identify anomalies in healthcare data and investigate these further to determine if they indicate fraudulent activity.
• Create complex models for specific analyses using technologies such as Python, R, SQL, and SAS.
• Extract and manipulate Medicare, Medicaid, and other healthcare claims data in a cloud environment using relevant software tools.
• Develop targeted analyses and related materials to support decision-making.
• Stay informed about Medicare and Medicaid policies and assess the impacts of any changes on fraud detection models.
• Contribute to testing sprints and project initiatives as a supportive team member.
• Provide subject matter expertise to Statistical and Data Analysts, helping them enhance their skills and ensuring the quality of project deliverables.
• Optionally lead a team by planning, coordinating, and documenting project activities, managing team dynamics, and maintaining direct communication with clients.
• Communicate effectively with both technical and non-technical users, explaining procedures and results clearly.
• Participate in team projects and brainstorming sessions to evaluate various methodologies for study designs.
• Keep up to date with industry changes, trends, best practices, and applicable regulations, and assess how these may impact your projects.
• Exercise discretion and independent judgment in alignment with company policies and practices.
  
  

Qualifications

• A minimum of a 4-year degree in statistics, mathematics, computer science, or a related field, or at least 6 years of data analysis experience in the healthcare sector.
• At least 6 years of professional experience with large and complex data sets, including a minimum of 3 years specifically in healthcare data analysis.
• Advanced knowledge of analytic, mathematical, and statistical methods.
• Familiarity with Medicare and Medicaid claims, including ICD10 codes, HCPCS, and Diagnosis Related Groups (DRG).
• Proficient in merging disparate datasets and using functions like INNER/LEFT/RIGHT joins, COALESCE(), CAST(), and SAS functions such as SUBSTR(), LAG(), and PROC SQL.
• Relevant experience in a health-related, scientific, or public policy/business discipline with a strong foundation in quantitative methods/statistical analysis.
• Proficiency in project software such as SAS/SQL, Python/PySpark, Snowflake, R, and Databricks, as well as Microsoft Office products like Excel, Word, PowerPoint, and Outlook.
• Strong understanding of analytic methodologies and principles.
• Respond promptly and cooperatively to tasks and requests.
• Demonstrate adaptability to change and proactively identify areas for improvement.
• A strong team player who collaborates effectively with colleagues to meet organizational needs.
• Ability to pass a public trust background check; a current public trust is preferred.
  
  

Additional Requirements

• Successful completion of post-hire background screening checks.
  
  

Employment Type: Full-Time