R Programming Lead (Statistical Programming)

Join a sponsor-dedicated team and contribute to the advancement of in-house study activities over time. As the R Programming Lead , you will provide technical expertise to the Statistical Programming team, ensuring the delivery of high-quality solutions that meet both internal and external requirements.

Responsibilities

• Develop internal and external R packages for clinical trial analysis (ADaM, tables, figures, listings).
• Validate R packages.
• Building complex R-Shiny applications (animations, dashboards) to address clinical questions, EU JCA requirements, and decision-making.
• Lead implementation in R and train other Biostatistics team members.
• Conduct statistical programming work of clinical data using R.
• Identifies problems and develops global tools that increase the efficiency and capacity of the Statistical Programming group.
• Create and/or validate all safety and efficacy study output requirements (e.g. ADaM, TLFs) consistent with data definitions and specifications and relevant study documentation (e.g. protocol, SAP, aCRF).
• Collaborates with peers and statisticians to ensure the quality and accuracy – thus submission readiness – of clinical data as required by authorities (i.e. SDTM, ADaM, tables, figures, listings, define.xml).

Experience And Qualifications

• Strong experience in R programming for clinical trial data including developing and validating R packages from CRO or Pharmaceutical Industry.
• Strong programming skills in R/R Shiny.
• Proven experience in applying R and R-Shiny for the analysis and reporting of clinical trials. Ability to reproduce statistical analysis using R.
• Strong skills in data visualization and data wrangling using R. Proficiency in using R packages for data exploration and visualization.
• Application of statistical methodology and concepts in clinical trial analysis. Experience with R-Shiny apps for data exploration.
• Advanced knowledge of industry standards including CDISC data structures as well as a solid understanding of the development and use of standard programs.
• Ability to conduct statistical programming of clinical data using R, and create/validate safety and efficacy outputs (ADaM, TLFs) aligned with study documentation (protocol, SAP, aCRF).
• Exposure to Late Phase, Real-World Evidence (RWE) & Global Medical Affairs studies is highly desirable.