Senior R Programmer/ Shiny Developer
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Overview
In this role you will design, build, and optimize interactive R Shiny applications that support clinical trial activities, enabling scalable data analysis and efficient regulatory reporting. You work within the Biostatistics team to deliver user-friendly tools for data exploration, quality control, and statistical review, while promoting reusable components and high-performance performance. You will help ensure compliance with GxP and CSA standards and contribute to open-source R/shiny initiatives.
Responsabilidades
- Design, develop, test, and maintain interactive R Shiny apps for clinical trial data analysis
- Create user-friendly tools for statistical review, data exploration, QC, and reporting
- Develop reusable Shiny modules and frameworks for consistency and efficiency
- Optimize performance, scalability, and usability of applications
- Build utilities using R, SAS, and Python
- Support SDTM/ADaM review, dataset comparison, metadata review, TLF review and QC, data visualization, and statistical reporting
- Ensure applications comply with GxP, CSA, and company standards
- Plan and execute unit, integration, and regression testing
- Provide technical consultation on R programming and Shiny development
- Develop programs supporting project deliverables (ADaM, TLFs) and assist study teams with programming activities
Requisitos principales
- 5+ years of programming experience in pharmaceutical/biotech/CRO environments
- 3+ years hands-on experience with R, R packages, RStudio, and RShiny in clinical data analysis
- Experience integrating Shiny apps with cloud data sources (AWS S3, Azure Data Lake)
- Ability to scale Shiny apps to hundreds of users and perform multi-level optimization
- Experience validating Shiny apps to meet FDA/EMA/GxP guidelines
- Proven track record building tools/pipelines that improve efficiency and standardization
- Active participation in open-source community related to R and Shiny
- Strong communication skills to translate technical strategy for technical and non-technical stakeholders
- Ability to work cross-functionally and influence product direction
- R, R packages, RStudio, and RShiny
- SAS
- Python
- Cloud data storage (AWS S3, Azure Data Lake)
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