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Position Title: Senior Manager, Statistical Programming

Department: Clinical Data Sciences & Analytics 

Reports To: Head of Statistical Programming

Location: South San Francisco, CA or Princeton, NJ - On-site 4 days per week (Mon to Thurs) 

Job Overview:

The Senior Manager of Statistical Programming will be responsible for leading Statistical Programming activities. It involves hands-on implementation of statistical analyses using SAS/R, as well as performing quality reviews of deliverables, both for in-house analyses and outsourced programming tasks.

This position serves as a critical bridge between Biostatistics and Clinical Data Management (CDM), ensuring the development of CRFs and the delivery of high-quality clinical data. Additionally, this position will play an important role in establishing SOPs and programming standards and modernizing statistical reporting with open-source tools.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Key Project Responsibilities:

• Provide programming leadership and oversee study to compound-level programming deliverables in collaboration with the lead biostatistician and cross-functional teams.
• Serve as the lead programmer to review the SAP, Data Presentation Plan, and Table Shells to align with project objectives and ensure clarity and completeness of programming assumptions and requirements.
• Lead programming team to produce and/or validate SDTM, ADaM, and TLF for CSR and regulatory requests, publication needs, and ad-hoc analyses.
• Manage CROs and contractors, ensuring compliance, quality of deliverables, timelines, and budget adherence.
• Collaborate with biostatisticians and clinical development colleagues to develop/review TLF shells, SDTM, and ADaM specifications.
• Work closely with Data Management and Biostatistics teams to ensure the accuracy of final databases, analyses, and reports.
• Develop company tools, such as R packages, macros, and interactive data dashboards (e.g., with Shiny), to enhance the efficiency and capacity of the Statistical Programming team.
• Develop robust programs to create define.xml. Lead the NDA eSubmission package preparation.
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Initiative Responsibilities:

• Under the guidance of the Head of Statistical Programming and Compound Lead, implement innovative strategies and technologies to enhance programming processes.
• Working with the manager, establish Statistical Programming standards and deploy programming strategies, specifications, and programmed analyses.
• Proactively plan, implement, and identify issues/risks and provide remediation strategies to improve programming capability.

Qualifications and Preferred Skills

Education:

• Master's degree in Statistics/Biostatistics, Mathematics, Computer Science, or a related field.

Experience and Skill Set:

• Minimum of 6 years of statistical programming experience in the pharmaceutical, biotech, or CRO clinical trial environment.
• Advanced SAS and R programming skills, with experience using Git for version control required. Extensive hands-on experience with SDTM, ADaM, and TLF programming.
• Python programming experience is desirable.
• Proficient knowledge in the implementation of CDISC standards (SDTM, ADaM) and regulatory submission requirements.
• Good knowledge of the drug development process, study design, statistical methodology, regulatory guidance, statistical concepts, and medical terminology.
• Broad expertise in statistical programming and in developing computing strategies.
• In-depth understanding of CDISC standards including SDTM and ADaM models and extensive experience with their implementation in clinical trials.
• Knowledge of data validation, define.xml generation using Pinnacle 21.
• Results-oriented, with proven problem-solving skills and a strong interest in continued learning.
• Excellent communication and collaboration skills, with the ability to work closely with cross-functional teams.
• Experience managing outsourced programming activities and overseeing deliverables from CROs and contractors.
• Adaptable and able to thrive in a fast-paced, startup environment while managing multiple priorities effectively.
• Experience with regulatory audits and inspections (e.g., FDA, PMDA, NMPA, EMA) is a strong advantage.