Position Description
We are seeking an experienced Contract Biostatistician to provide statistical leadership across clinical development, evidence generation, and scientific publication activities. This individual will play a key role in the design, analysis, interpretation, and communication of clinical and observational data, with particular emphasis on meta-analyses, external comparator analyses, evidence generation, and advanced statistical methodologies.
The ideal candidate will have a strong background working with clinical trial data while also bringing experience supporting Real-World Evidence (RWE) initiatives and Medical Affairs projects. This position will collaborate closely with cross-functional teams, including Clinical Development, Medical Affairs, Health Economics & Outcomes Research (HEOR), Regulatory Affairs, and Commercial, to support strategic analyses that inform clinical development, publications, and scientific decision-making.
Responsibilities and Duties
- Provide statistical leadership for clinical development and evidence generation projects utilizing both clinical trial and real-world data.
- Provide statistical expertise in analyses involving external control arms, synthetic control methodologies, external comparator analyses, meta-analyses, and causal inference methods (e.g., propensity score matching, inverse probability weighting, and related methodologies).
- Lead or support evidence generation activities to address scientific, clinical, and strategic research questions.
- Partner with cross-functional teams to support scientific publications, including manuscripts, abstracts, posters, and conference presentations.
- Provide statistical support for publication strategy and execution.
- Contribute statistical expertise to Medical Affairs and Real-World Evidence initiatives, as appropriate.
- Collaborate with Clinical Development teams on study design, protocol review, endpoint selection, and statistical methodology.
- Develop Statistical Analysis Plans (SAPs), TLF shells, and review programming specifications.
- Work closely with statistical programmers to conduct analyses, review programming deliverables, and ensure the quality and accuracy of statistical outputs.
- Perform statistical programming for advanced analyses, as needed.
- Review relevant medical and scientific literature to support evidence generation strategies and methodological approaches.
- Ensure all statistical analyses are conducted with scientific rigor and in accordance with applicable regulatory requirements and industry standards.
Minimum Requirements
Experience
- M.S. or Ph.D. in Biostatistics (or equivalent) with 5+ years of pharmaceutical, biotechnology, or related industry experience.
- Strong experience analyzing and interpreting clinical trial data across multiple phases of drug development.
- Experience supporting evidence generation through advanced statistical methodologies.
- Demonstrated expertise conducting meta-analyses, external comparator analyses, indirect treatment comparisons, pooled analyses, and causal inference analyses.
- Experience working with Real-World Evidence (RWE) datasets and supporting Medical Affairs initiatives is preferred.
- Experience supporting scientific publications, including manuscripts, abstracts, and conference presentations.
Other Qualifications
- Strong understanding of advanced statistical methodologies and evidence synthesis techniques.
- Familiarity with regulatory expectations related to clinical research; knowledge of RWE and HTA guidance is a plus.
- Excellent statistical reasoning, analytical problem-solving, and scientific communication skills.
- Ability to effectively communicate complex statistical concepts to cross-functional stakeholders.
- Strong statistical programming skills using SAS, R, or other relevant statistical software.
- Experience writing Statistical Analysis Plans (SAPs) and developing TLF specifications.
- High attention to detail and commitment to methodological rigor and data quality.
- Ability to work independently in a fast-paced, collaborative environment.
- Solid understanding of Good Clinical Practice (GCP) guidelines.
- Oncology experience preferred.