Sr RWE Statistical Analyst/Programmer

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Sr. RWE Statistical Analyst/Programmer 
Overview
This is a remote, full-time role embedded within an HEOR Value and Access function, split approximately 75% statistical programming, 15% biostatistics consulting, and 10% medical communications support. The team executes RWE studies supporting product registration, reimbursement, market access, and competitive differentiation across a rare disease portfolio. The ideal candidate brings strong hands-on programming skills alongside the statistical depth to engage meaningfully on methods, study design, and analytical strategy in a fast-moving, cross-functional environment.

Responsibilities

• Write, execute, QC, and tidy SAS and/or R programs for RWE analyses
• Conduct SQL queries against raw data sources including claims, EHR, and other real-world datasets
• Manipulate and validate large healthcare datasets to support study deliverables
• Interpret analytic requests and study specifications; proactively clarify requirements to ensure accurate implementation
• Contribute to statistical methods development and review of Statistical Analysis Plans (SAPs)
• Provide biostatistics consulting support, including cost and HCRU analyses, and RWE methodology
• Support development of final study summary decks and topline analytical deliverables
• Contribute to abstract, poster, and manuscript development
• Work independently and efficiently against tight timelines with shifting priorities

Minimum Qualifications

• Master’s degree in Biostatistics, Epidemiology, Public Health, or related quantitative field
• 3+ years of hands-on experience with large-scale RWD sources; claims analyses experience required. Familiarity with patient registry and EHR data preferred. 
• Proficiency in SAS and/or R; comfort working with raw data and SQL
• Working knowledge of common statistical methods including generalized linear models and cost/HCRU analytic approaches

Preferred Qualifications

• Experience reviewing or contributing to SAPs in an RWE or outcomes research context
• Familiarity with RWE study design and methods (e.g., PSM, IPTW, comparative effectiveness)
• Experience contributing to abstracts, posters, or peer-reviewed manuscripts in an outcomes research setting
• Ability to communicate statistical concepts clearly to cross-functional stakeholders

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