Global Lead Statistical Programmer

About the job

Job DescriptionAs a Global Lead Statistical Programmer, you will play a pivotal role in leading programming activities for various clinical studies and projects. Your primary responsibility will be to oversee the implementation of programming and project standards, ensuring timely and high-quality deliverables. Lead statistical programming activities for therapeutic areas or compounds/indications within multiple studies/projects. Develop and maintain programming documentations following established standards and processes. Create CDISC standard SDTM mapping specifications and ADaM specifications.Key Roles and Responsibilities Develop and oversee the development of SAS programs for creating SDTM and ADaM datasets. Contribute to the establishment and maintenance of statistical programming standards. Participate in CRF annotation, SAP review, TLFs specifications development, and TLFs review. Handle P21 related items and eCRT packages, including aCRF, define.XML, cSDRG, ADRG, and ARM for regulatory submissions. Support global regulatory authority submissions, working closely with partnering functions to address health authority requests. Qualification, Skills, and Competencies Requirements Minimum Bachelor's degree in Statistics, Computer Science, Mathematics, Engineering, Life Science, or related discipline with 7-8+ years of programming experience in processing clinical trial data. Oncology therapeutic area preferred. Strong SAS programming skills in a clinical data environment, with excellent analytical skills. Good knowledge of pharmaceutical clinical development and regulatory submissions (NDA, ANDA). Ability to work independently and on global interdisciplinary teams, with good organizational, interpersonal, and communication skills.

Requirements

• SAS
• Statistical Programming
• Clinical Trials
• Oncology

Qualifications

• Bachelor's degree in Statistics, Computer Science, Mathematics, Engineering, Life Science, or related discipline

Preferred Technologies

• SAS
• Statistical Programming
• Clinical Trials
• Oncology