Biostatistician Contractor

Key Responsibilities

• Partner with Medical Affairs to support publication strategies and evidence-generation initiatives.
• Collaborate with HEOR teams to provide statistical input for economic models and outcomes research analyses.
• Provide statistical expertise for observational research, external and synthetic control analyses, meta-analyses, and causal inference methodologies, including propensity score-based approaches.
• Contribute to scientific manuscripts, abstracts, posters, presentations, and other evidence dissemination activities.
• Collaborate with HEOR stakeholders to ensure analyses align with health technology assessment (HTA) expectations and payer evidence requirements.
• Review and provide statistical input on protocols for real-world evidence studies.
• Partner with statistical programmers to conduct ad hoc analyses and perform quality review of statistical outputs.
• Perform statistical programming for advanced analytical methods and support quality control of programming deliverables.
• Review relevant scientific and medical literature to inform study design and analysis strategies.
• Develop statistical analysis plans (SAPs) and related study documentation.
• Create table, listing, and figure (TLF) shells and review programming specifications.

Qualifications

Education & Experience

• M.S. in Biostatistics, Statistics, or a related quantitative discipline with a minimum of 5 years of pharmaceutical, biotechnology, healthcare, or related industry experience; or
• Ph.D. in Biostatistics, Statistics, or a related quantitative discipline with relevant industry experience.

Preferred Skills & Expertise

• Experience supporting Medical Affairs, HEOR, or evidence-generation functions within the life sciences industry.
• Strong understanding of observational research methodologies, meta-analysis techniques, and causal inference approaches.
• Familiarity with regulatory and industry guidance related to real-world evidence and health technology assessment requirements.
• Strong statistical reasoning, analytical problem-solving, and study design capabilities.
• Ability to effectively communicate complex statistical concepts to non-statistical audiences.
• Demonstrated commitment to methodological rigor and data quality.
• Ability to work independently and manage multiple priorities in a fast-paced, cross-functional environment.
• Understanding of Good Clinical Practice (GCP) guidelines and applicable industry standards.
• Proficiency with statistical programming software such as SAS, R, or equivalent platforms.
• Experience in oncology or other complex therapeutic areas is preferred.