Sr. Manager, Statistical Programming

Job Description

Overview of Role:

The Senior Manager, Statistical Programming will be responsible for leading and managing the statistical programming activities for clinical trial data collection, analysis, reporting, and visualization, with a primary focus on oncology studies. This role will oversee the development and implementation of statistical programming strategies, manage a team of statistical programmers, and collaborate closely with cross‑functional teams to ensure high‑quality deliverables that meet regulatory requirements and support drug development efforts.

Role and Responsibilities:

• Lead and manage statistical programmers, providing mentorship, technical guidance, and career development opportunities.
• Develop and implement statistical programming strategies and best practices for clinical trials across all phases, ensuring alignment with company goals, industry standards, and regulatory requirements.
• Oversee the creation and validation of CDISC‑compliant SDTM and ADaM datasets, with a focus on oncology‑specific data structures and endpoints.
• Collaborate with Biostatistics to implement complex statistical analyses for oncology trials, including time‑to‑event analyses, response evaluations, and biomarker assessments.
• Direct the development of tables, listings, and figures (TLFs) for clinical study reports, regulatory submissions (including NDA/BLA), and publications.
• Ensure compliance with FDA, EMA, PMDA and other regulatory agency requirements for statistical programming deliverables in submissions.
• Lead the development and maintenance of standardized oncology‑specific analysis datasets, programs, and macros to improve efficiency and consistency across projects.
• Manage resource allocation, project timelines, and deliverables for multiple studies simultaneously, including outsourced work to CROs.
• Serve as the statistical programming representative in cross‑functional study teams and external collaborations.
• Contribute to the development and improvement of department SOPs, working instructions, and quality control processes.
• Stay current with evolving trends in oncology clinical trials, statistical methodologies, and programming techniques, and implement innovative approaches as appropriate.
• Contribute to regulatory interactions and represent statistical programming in regulatory meetings when needed.

Experience, Education and Specialized Knowledge and

Skills:

• Master’s degree in Statistics, Biostatistics, Computer Science, or a related field.
• Minimum 10 years of experience in statistical programming within the pharmaceutical/biotech industry, with at least 5 years focused on oncology trials and 3+ years in a leadership role.
• Extensive experience with CDISC standards (SDTM, ADaM, define.xml) and their application in clinical studies across all phases.
• Strong proficiency in SAS programming, including macro development, ODS graphics, and experience with SAS/STAT procedures.
• In‑depth knowledge of oncology‑specific endpoints, such as progression‑free survival (PFS), overall survival (OS), objective response rate (ORR), and RECIST criteria.
• Experience with statistical analysis methods commonly used in oncology trials, including time‑to‑event analyses and methods for handling missing data.
• Thorough understanding of regulatory requirements for statistical programming in submissions to FDA, EMA, PMDA, and other health authorities.
• Experience in preparing and reviewing key documents for regulatory submissions (e.g., SAP, ADaM spec, Define files, Reviewer's Guide).
• Demonstrated experience in leading and managing statistical programming teams, including experience with global and/or outsourced teams.
• Strong project management skills, with the ability to prioritize and manage multiple studies simultaneously.
• Excellent problem‑solving skills and the ability to provide innovative solutions to complex programming challenges in clinical research.
• Strong communication skills, both written and verbal, with the ability to effectively communicate technical concepts to non‑technical stakeholders.
• Experience with R and Python programming languages is highly desirable.
• Familiarity with data standards organizations (e.g., CDISC,…