Director, Statistical Programming

Role Summary

Director, Statistical Programming overseeing programming strategy, team leadership, and regulatory submission support within BioNTech's clinical operations. Focused on SDTM/ADaM, TLFs, and advanced analytics adoption across global studies and submissions.

Responsibilities

• Partner with Head of Statistical Programming to define and execute a comprehensive programming strategy, including vendor oversight, process automation, and adherence to industry standards.
• Lead and oversee a team of internal/FSP programmers and CROs to ensure timely, high-quality delivery of analysis datasets, tables, listings, and figures (TLFs).
• Drive the creation, review, and validation of SAS/R programs for SDTM/ADaM datasets, efficacy/safety outputs, and integrated summaries, ensuring reproducibility and compliance with SOPs and regulatory standards.
• Collaborate with Biostatistics, Clinical Development, Data Management, and Regulatory Affairs to influence study designs, statistical analysis plans, and submission strategies.
• Lead the programming contribution to global regulatory submissions (NDA, BLA, MAA), including submission ready datasets, TLFs, define.xml, and reviews’ guide.
• Champion adoption of advanced analytics, automation, and emerging technologies (e.g., R, Python, AI/ML) to optimize workflows and mentor teams on industry innovations.
• Establish and maintain robust programming processes, infrastructure, and SOPs to enhance efficiency and standardization across studies and submissions.
• Contribute to continuous improvement and global clinical initiatives to strengthen BioNTech’s clinical operation and data analysis capabilities.

Qualifications

Education

• Bachelor’s degree in Statistics, Mathematics, Computer Science or related discipline, advanced degree preferred

Experience

• 15+ years (10+ years for advanced degree) experience in a pharmaceutical industry, CRO or another clinical research setting, with a focus on oncology.
• Expert knowledge of statistical programming in SAS (Base, Macro, STAT, GRAPH, SQL).
• Solid understanding of FDA, EMA, ICH, and global regulations and guidelines.
• Deep knowledge of clinical study data standards and reporting requirements, including CDISC (SDTM and ADaM).
• Thorough understanding of the drug development process across early- to late-stage development and submission.
• Demonstrated expertise in supporting electronic submissions (eCDT, define.xml, reviewer’s guides).
• Proven project management skills with the ability to oversee multiple concurrent projects and global vendors.

Skills

• Strong leadership and people management
• Project management and vendor oversight
• Regulatory submission preparation and review
• Advanced programming in SAS; familiarity with R/Python
• Process improvement and SOP development

Education

• Bachelor’s degree in Statistics, Mathematics, Computer Science or related discipline; advanced degree preferred