Data Scientist – Medicare Part D, Market Access

• Apply real-world data and advanced healthcare analytics to answer complex questions influencing how innovative therapies are evaluated, valued, reimbursed, and accessed
• Develop, validate, and deploy predictive and statistical models in Python or R to forecast prescription drug spending, patient utilization, and market shifts
• Analyze Prescription Drug Event (PDE) claims, formulary tier structures, and beneficiary out-of-pocket costs to optimize plan performance and market positioning
• Query, clean, and synthesize massive, unstructured administrative healthcare datasets, including public and restricted CMS data files, using SQL and cloud data platforms
• Build data-mining algorithms to identify market anomalies, track attrition rates, and detect potential fraud, waste, or abuse
• Partner with market access professionals, health economists, and consulting associates to translate analytical findings into strategic reports
• Adapt existing data models to reflect changing federal healthcare regulations, benefit redesigns, and modern payment structures
• Design and conduct analyses using Medicare, Medicaid, commercial claims, pharmacy, EHR, and other real-world healthcare data
• Work extensively with CMS data, including PDE data, CCW, VRDC, and other Medicare and Medicaid data sources
• Develop and maintain analytical programs using SAS
• Contribute to observational research and real-world evidence studies supporting life sciences clients
• Support client-facing presentations, reports, exhibits, and other deliverables
• Communicate complex analytical concepts and findings to technical and non-technical audiences
• Apply programming, documentation, validation, and quality assurance practices
• Contribute to projects spanning market access, reimbursement, pricing, healthcare policy, and value strategy

Requirements

• Bachelor’s degree in Computer Science, Data Science, Biostatistics, Epidemiology, Public Health, Health Economics, or another quantitative discipline
• Hands-on experience working with Medicare PDE data is required
• Professional experience using SAS
• Experience in healthcare analytics, HEOR, RWE, observational research, or a related field
• Experience working with healthcare claims and pharmacy data
• Familiarity with Medicare and Medicaid data, reimbursement, and healthcare policy
• Experience with CMS Chronic Conditions Warehouse (CCW), Virtual Research Data Center (VRDC), T-MSIS, or similar healthcare data environments
• Strong analytical, problem-solving, and communication skills
• Ability to work collaboratively in a consulting environment and manage multiple project priorities
• Candidates must be legally authorized to work full time in the United States at the time of their hire
• ADVI does not offer employment sponsorships now or in the future
• Proficiency or experience with Python, R, SQL, SAS, Medicare PDE, CCW, VRDC, T-MSIS, healthcare claims, pharmacy data, and CMS data sources

Core Competencies

Demonstrates expertise in healthcare analytics, predictive modeling, and data management, with a strong focus on utilizing Python, R, SQL, and SAS to analyze complex healthcare datasets. Proven ability to communicate analytical findings effectively to diverse audiences and adapt to evolving healthcare regulations.

Highest-signal resume keywords

• Healthcare Analytics
• Predictive Modeling
• SAS Programming
• Medicare PDE Data
• SQL Data Management

Hard Skills

• Python
• R
• SAS
• SQL
• Predictive Modeling
• Statistical Analysis
• Data Mining
• Data Cleaning
• Healthcare Claims Analysis
• Market Access Strategy

Soft Skills

• Analytical Skills
• Problem-Solving
• Communication Skills
• Collaboration
• Project Management

Industry Keywords

• Real-World Evidence (RWE)
• Health Economics
• Observational Research
• Reimbursement
• Healthcare Policy

Tools & Technologies

• CMS Data Sources
• Chronic Conditions Warehouse (CCW)
• Virtual Research Data Center (VRDC)
• T-MSIS
• Public Health Data