Senior Manager, Biostatistics

Overview:

The Senior Manager, Biostatistics provides statistical leadership for complex clinical studies in cell therapy oncology programs. Responsible for study design, statistical analysis, interpretation of results, and communication of statistical findings.

• Serve as lead statistician for one or more clinical studies and may support program-level statistical strategy.
• Lead statistical activities for assigned studies; collaborate with statistical programmers and CRO partners to deliver timely, high-quality statistical outputs.
• Author and review statistical sections of study protocols, statistical analysis plans, clinical study reports, regulatory submission documents, and publications (abstracts/posters).
• Maintain current knowledge of statistical methodologies, regulatory guidance, and oncology drug development best practices.
• Contribute statistical expertise to due diligence and cross-functional evaluations as needed.
• Create networks with external statistical/programming collaborators and influence internal decisions to ensure quality of study designs/analyses and appropriate conclusions.
• Contribute to process improvements, standards development, and statistical best practices within Biostatistics.
• Work effectively in cross-functional teams to resolve study-level operational and scientific challenges.
• Contribute to knowledge sharing within the department.

• Ph.D. in Statistics/Biostatistics (3–5 years relevant industry experience in healthcare) or M.S. (6–8 years relevant industry experience in healthcare).
• Strong experience in oncology clinical development (design and analysis of early- and late-phase trials).
• Sound theoretical/applied statistics knowledge (including survival analysis, patient-reported outcomes, health economics).
• Strong decision-making with cross-functional/global perspective; can operate with limited/ambiguous information.
• Strong verbal, written, and presentation skills.
• Experience leading collaborative efforts to obtain/analyze complex data.
• Proficiency in SAS; R familiarity highly desirable.

• Working knowledge of FDA/EMA/ICH statistical guidance; regulatory submission experience (NDA/BLA/MAA) preferred.

Professional office or remote work environment; routine use of standard office equipment and technology.