Senior Principal Statistical Programmer

Role Summary

Onsite East Hanover, New Jersey. The Statistical Programming community at Novartis comprises approximately 350 internal statistical programmers within the Advanced Quantitative Sciences (AQS) organization, alongside more than 450 biostatisticians, pharmacometricians, and data scientists supporting the clinical project portfolio across Research, Development, and Commercial. You will be responsible for all statistical programming (SP) aspects of several studies, a medium to large sized program or program-level activities (including submission and post-marketing activities). You will be a key collaborator and strategic partner with cross-functional team members within the clinical trial/program, ensuring integrated development/evidence plans are executed efficiently with timely and high-quality deliverables.

Responsibilities

• Lead statistical programming activities as a trial programmer for one or multiple trials or as a lead/program programmer for a program or indication.
• Coordinate activities of internal or external programmers; make SP decisions and propose strategies at study, program or indication/disease level.
• Act as functional manager of associates, providing supervision and guidance to programmers on operational/functional expertise and processes.
• Build and maintain effective working relationships with cross-functional teams, summarizing and discussing status of deliverables and critical programming aspects (timelines, scope, resource plan) as a programming representative in study- or program-level teams.
• Review eCRF, data structures, and ensure program-level standardization for effective pooling and efficient case record tabulation (CRT) production.
• Comply with company, department, and industry standards (e.g., CDISC); assess and clarify additional programming requirements, review, develop, and influence programming specifications as part of the analysis plans (including program-level strategies).
• Provide and implement statistical programming solutions; ensure knowledge sharing. Act as programming expert in problem-solving aspects.
• Ensure timely and quality development and validation of datasets and outputs for CSRs, regulatory submissions/interactions, safety reports, publications, post-marketing activities, or exploratory analyses as required.
• Responsible for quality control and inspection readiness of all assigned statistical programming deliverables and the accuracy and reliability of statistical analysis results.
• Maintain up-to-date advanced knowledge of programming software (e.g., SAS, R) and industry requirements (e.g., CDISC, eCTD, Define.xml); may act as SME on process improvement/non-clinical initiatives with a focus on programming.

Qualifications

• Essential: BS degree in statistics, computer science, mathematics, life science, or equivalent; 7+ years in a programming role, preferably supporting clinical trials or in the pharmaceutical industry.
• Essential: Experience as Trial/Lead/Program Programmer for multiple studies or project-level activities, including coordinating a team of internal or external programmers; ability to transfer knowledge to others.
• Essential: Expert SAS/R experience with proven skills to develop and validate deliverables; proven experience in development of advanced MACROs.
• Essential: Advanced experience contributing to statistical analysis plans and/or constructing technical programming specifications.
• Essential: Advanced knowledge of CDISC data structures and a solid understanding of the development and use of standard programs.
• Essential: Good understanding of regulatory requirements relevant to Statistical Programming (e.g., GCP, study procedures).
• Essential: Proven communication and negotiation skills; ability to work well with others globally and influence.
• Preferred: MS or Ph.D. in statistics, computer science, mathematics, life science, or equivalent.

Education

• Required: BS degree in statistics, computer science, mathematics, life science, or equivalent.
• Preferred: MS or Ph.D degree in statistics, computer science, mathematics, life science, or equivalent.