Senior Director, Biostatistics

Key Position Responsibilities

• Provide statistical leadership for clinical development programs from early-stage planning through registrational studies and regulatory submission, shaping development plans, endpoint strategies, evidence-generation plans, and program-level statistical approaches.
• Translate program objectives into statistically robust and operationally feasible trial designs, including strategies for sample size, randomization, estimands, multiplicity, interim analyses, missing data, sensitivity and subgroup analyses, and benefit-risk assessment.
• Apply innovative approaches to rare disease development, including the appropriate use of natural history data, external controls, Bayesian methods, and other external information to address small sample sizes, disease heterogeneity, limited concurrent controls, and evolving standards of care.
• Partner with Clinical Development, Translational Sciences, and external collaborators to leverage biomarker, natural history, and other external data sources in support of clinical development decisions.
• Lead or oversee statistical content for protocols, Statistical Analysis Plans, interim analysis plans, randomization specifications, case report forms, data review plans, table/listing/figure shells, clinical study reports, publications, and related study documents.
• Provide statistical leadership throughout study conduct, including data review, protocol amendments, analysis decisions, exploratory and ad hoc analyses, and interpretation of emerging results, while ensuring analyses are reproducible, appropriately documented, and compliant with regulatory requirements and industry standards.
• Develop and defend statistical strategies for global health authority interactions and submissions, including briefing documents, agency responses, meeting packages, integrated summaries of efficacy and safety, and clear communication of study designs, methods, and results in regulatory meetings.
• Provide strategic and technical oversight of outsourced biostatistics, establishing expectations for quality, timelines, documentation, communication, and issue escalation; review and approve vendor deliverables and proactively address statistical and programming risks.
• Maintain knowledge of evolving regulatory expectations for rare diseases, gene therapies, and advanced therapeutics, and influence program decisions by communicating complex statistical concepts, risks, assumptions, and alternatives clearly to technical and nontechnical stakeholders.

Experience Requirements

• PhD in Biostatistics, Statistics, or a related quantitative discipline strongly preferred; an MS degree with substantial relevant industry and leadership experience may be considered.
• Typically at least 12 years of biopharmaceutical industry experience with progressively increasing responsibility in clinical development.
• Demonstrated experience supporting global health authority interactions and regulatory submissions, including preparation of statistical content, responses to agency questions, and BLA, NDA, MAA, or comparable filings.
• Experience in rare disease, gene therapy, neuromuscular disease, pediatric development, or other orphan indications strongly preferred, including addressing small populations, disease heterogeneity, natural history comparisons, external controls, and limited concurrent control data.
• Deep expertise in clinical trial design and statistical methods, including estimands, multiplicity control, missing data, longitudinal and time-to-event analyses, sensitivity analyses, and interpretation of efficacy and safety outcomes; experience with Bayesian borrowing, adaptive designs, causal inference, or other innovative rare disease approaches is preferred.
• Experience leading outsourced biostatistics and statistical programming activities, including CRO oversight, vendor governance, and review of external deliverables.
• Strong understanding of global regulatory expectations and relevant guidance, including ICH E9 and E9(R1), CDISC standards including SDTM and ADaM, and regulatory submission data requirements; proficiency with R and familiarity with SAS-based regulatory analysis and submission environments.