Principal Statistical Programmer

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 relationships 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. Understand Git-based version control workflows and their role in supporting collaborative, traceable, and reproducible programming activities.

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. Champion reproducibility, documentation, and code quality across programming activities; establishes best practices for code development, review, testing, and maintenance.

Maintain up-to-date advanced knowledge of statistical programming languages (e.g. R, SAS) as well as industry requirements, support and guide the application of modern programming practices in assigned studies or projects (e.g. CDISC SDTM/ADaM, eCTD, Define.xml) and attend functional meetings and training.