Sr. Manager, Biostatistician / Programmer
- Develop, validate, and maintain high-quality Tables, Figures, and Listings (TFLs) to support ongoing clinical trials, interim analyses, and internal/external deliverables in compliance with study requirements and standards.
- Perform hands-on statistical programming and data manipulation to support planned and ad hoc analyses, addressing evolving clinical and scientific questions.
- Independently explore and interrogate clinical trial data to identify trends, anomalies, and insights that support clinical interpretation and decision-making.
- Collaborate closely with Biostatistics, Clinical Development, Clinical Operations, Data Management,
- Translational research and Medical teams to ensure alignment of analyses with protocol objectives and clinical intent.
- Apply a strong understanding of therapeutic area, disease biology, and clinical endpoints to translate data into meaningful scientific insights.
- Contribute to analysis datasets, program specifications, programming documentation, and quality control activities in accordance with internal standards and regulatory expectations.
- Support process improvement initiatives, including enhancing programming efficiency, standardization, and reproducibility across studies and programs.
- This role operates with a high degree of autonomy in determining programming approaches, exploratory analyses, and data interrogation strategies to answer clinical questions. The Sr. Manager may independently make decisions related to analysis methods, programming solutions, prioritization of tasks, and investigative follow-up of data issues. Escalation and alignment are expected for changes impacting study-level strategy, major deliverables, timelines with external visibility, or regulatory-facing outputs.
- Master's degree or PhD in Statistics, Biostatistics, Mathematics, Data Science, or a related quantitative discipline.
- Demonstrated hands-on experience developing TFLs and performing ad hoc and exploratory analyses for clinical trials.
- Strong understanding of clinical trial design, clinical data structures, and the medical context behind analyses.
- Proven ability to work independently, manage ambiguity, and drive self-directed discovery from data.
- Experience supporting oncology and/or cell therapy programs is strongly preferred.
- Advanced proficiency in SAS for clinical trial analysis and reporting.
- Working knowledge of R for exploratory analyses and data visualization
- Strong experience with clinical data standards (e.g., SDTM, ADaM)
- Experience with or strong willingness to leverage AI-assisted programming tools to accelerate development, enhance code quality, and support efficient generation of Tables, Figures, and Listings (TFLs).
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