Description:
This key role is responsible for all statistical programming aspects of a large/pivotal study, several studies or project-level activities (incl. submission activities). The position is a key collaborator with biostatistics in ensuring that pharmaceutical drug-development plans are executed efficiently with timely and high-quality deliverables in Novartis Global Drug Development.
Key Responsibilities:
- Lead statistical programming activities as Trial Programmer for either a large/pivotal study or several studies, or act as a Lead/Program Programmer for a small to medium sized project in phase I to IV clinical studies in Novartis Global Drug Development.
- Co-ordinate activities of all programmers either internally or externally assigned to the study/project work, mentor other programmers in functional expertise and processes. Make statistical programming decisions/recommendations at study or project level.
- Build and maintain effective working relationship with cross-functional teams, able to summarize and discuss status of deliverables and critical programming aspects (timelines, scope, resource plan), e.g. as member of the extended Clinical Trial Team (CTT).
- Review eCRF, discuss data structures and participate in data review activities as member of the extended CTT.
- Comply with company, department and industry standards (e.g. CDISC) and processes, assess and clarify additional programming requirements at project-level, review and develop programming specifications as part of the analysis plans.
- Provide and implement statistical programming solutions; ensure knowledge sharing.
- In consultation with the Statistician, responsible for development of programming specifications of analysis datasets and pooled datasets.
- Ensure timely and quality development and validation of datasets and outputs for CSRs, regulatory submissions/interactions, safety reports, publications or exploratory analyses (as required) in the assigned drug development study/project according to specifications.
- Responsible for quality control and audit readiness of all assigned statistical programming deliverables as well as accuracy and reliability of statistical analysis results.