Data Scientist – Medicare Part D, Market Access

Stellenbeschreibung:

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.