Clinical R Programmer Consultant
J
JobgetherLife Sciences
United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 2+ years
- Required Skills
- GitR
Requirements
- Bachelor’s or Master’s degree in Statistics, Computer Science, Mathematics, Life Sciences, or a related technical field.
- 2+ years of experience in clinical programming, with a strong focus on R-based development.
- Demonstrated experience creating SDTM and ADaM datasets using R.
- Working knowledge of SAS programming in a clinical research environment.
- Strong understanding of CDISC standards, including SDTM and ADaM.
- Experience supporting clinical trial data, regulatory submissions, and quality control processes.
- Strong analytical, problem-solving, and documentation skills.
- Ability to write clear, maintainable, and reproducible programming code.
- Experience with R packages such as tidyverse, haven, pharmaverse tools (including admiral or tidyCDISC), or similar clinical programming frameworks preferred.
- Knowledge of R Markdown, Shiny applications, or reproducible reporting solutions preferred.
- Exposure to GxP validation practices, Git/version control, and automated workflows preferred.
- Previous experience within a CRO, pharmaceutical, biotechnology, or healthcare environment is a plus.
Responsibilities
- Develop, validate, and maintain SDTM and ADaM datasets using R while following CDISC standards and clinical programming best practices.
- Create and maintain efficient, reproducible R scripts for clinical data analysis, reporting, and automation workflows.
- Support the generation of tables, listings, and figures (TLFs) using R and SAS when required.
- Collaborate with statisticians, clinical data managers, and cross-functional teams to understand programming requirements and deliver high-quality outputs.
- Perform quality control checks, investigate data discrepancies, and ensure programming deliverables meet regulatory expectations.
- Support clinical trial programming activities, documentation, and version control processes.
- Contribute to the development and improvement of R-based programming pipelines and automation solutions.
- Apply knowledge of regulatory standards, including FDA and EMA expectations, to ensure compliant clinical data outputs.
- Utilize SAS programming capabilities to support legacy studies and additional programming needs.
- Promote reproducible programming practices through structured workflows, documentation, and efficient code development.
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