Sr. Manager, Statistical Programming

Proclinical Staffing; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Proclinical is seeking a Sr. Manager, Statistical Programming to lead and provide technical expertise across multiple clinical development programs within a specific therapeutic area.

This is a full-time position with the flexibility to work remotely. You will guide statistical programming activities, ensure timely, high-quality deliverables for internal teams and external vendors, and support global regulatory submissions.

Qualifications

• Advanced proficiency in SAS programming in a clinical research environment.
• Strong knowledge of CDISC SDTM and ADaM standards.
• Experience developing SDTM/ADaM datasets and reports.
• Experience supporting regulatory submissions (NDA/sNDA).
• Excellent collaboration and stakeholder management across international teams.

Responsabilités

• Lead statistical programming for multiple studies and programs.
• Ensure timely, high-quality programming deliverables from internal or vendors.
• Standardize processes and execution of programming activities.
• Oversee programming for global regulatory submissions and responses.
• Manage outsourced programming to meet budgets and timelines.
• Review TLFs, SDTM/ADaM datasets, and XML documentation.
• Contribute to SOPs, validation processes, and best practices.
• Maintain study documentation for regulatory audits.
• Identify opportunities to optimize workflows and adopt innovative approaches.

Connaissances

SAS programming

CDISC SDTM/ADaM

Regulatory submissions

Mentoring

Stakeholder management

Formation

Master's degree in Statistics

Outils

R

Description du poste

Ready to lead the statistical programming strategy behind innovative clinical development programmes and global regulatory submissions?

Proclinical is seeking a Sr. Manager, Statistical Programming to lead and provide technical expertise across multiple clinical development programs within a specific therapeutic area. This is a full-time position with the flexibility to work remotely.

Responsibilities:

• Lead statistical programming activities for multiple clinical studies and development programs.
• Ensure timely delivery of high-quality programming deliverables, whether produced internally or by external vendors.
• Maintain consistency in processes, standards, and execution of programming activities across assigned studies.
• Support and oversee programming activities related to global regulatory submissions and responses to health authorities.
• Manage outsourced programming activities, ensuring adherence to quality, budget, and timelines.
• Review and supervise the production of programming deliverables, including:
• Tables, Listings, and Figures (TLFs)
• SDTM and ADaM datasets
• xml files and associated documentation
• Contribute to the development, implementation, and continuous improvement of programming standards, SOPs, validation processes, and best practices.
• Maintain study documentation in compliance with regulatory requirements, ensuring audit and inspection readiness.
• Identify opportunities to optimize workflows, promote innovative approaches, and address programming needs for increasingly complex study protocols and methodologies.

Key Skills and Requirements:

• Advanced proficiency in SAS programming within a clinical research environment.
• Strong knowledge of CDISC standards, including SDTM and ADaM.
• Proven experience in developing and programming SDTM and ADaM datasets.
• Expertise in generating reports, TLFs, and other statistical outputs.
• Experience supporting clinical development programs and trials.
• Familiarity with regulatory submission processes (e.g., NDA, sNDA, or equivalent).
• Strong collaboration and communication skills, with the ability to work effectively in multidisciplinary and international teams.
• Proactive stakeholder management and decision-making abilities.
• Excellent planning, organizational, and prioritization skills.
• Ability to mentor, train, and influence team members and project teams.
• Knowledge of R or other statistical programming tools is a plus.
• Solid understanding of the clinical data lifecycle and data management processes.
• Educational background in Statistics, Mathematics, Computer Science, Life Sciences, or a related field (Master's degree preferred; Bachelor's degree considered with relevant experience).