> Markdown version of [/jobs/ext/4362230-senior-statistical-programmer-r](https://www.wearedevelopers.com/jobs/ext/4362230-senior-statistical-programmer-r). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Statistical Programmer (R)

- **Company:** Simulstat Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Data Analysis, Data Visualization, Linux, R (Programming Language), Package Development Process, SAS (Software), Shell Script, Software Engineering, GXP
- **Published:** October 6, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a390d325461155d3

## About the Role

* BS/MS in Statistics, Biostatistics, Mathematics, or related field
 * 5+ years of statistical programming experience in pharma/biotech
 * Strong R programming skills, including tidyverse, RMarkdown/Quarto, and Git/GitHub
 * Experience producing ADaM datasets and TLFs in R, ideally with pharmaverse packages (admiral, rtables/tern)
 * Applied experience with CDISC SDTM/ADaM
 * SAS experience, to work alongside existing SAS code

Additional skills

 * Shiny app development a plus, including user access control (e.g., rAccess, shinymanager, Posit Connect) and app deployment
 * R package development, GxP validation, and Linux/shell scripting experience a plus

## Description

Clinical statistical programmer with hands-on ADaM/TLF production and validation experience in R, supporting clinical study reporting alongside existing SAS workflows., * Develop and validate ADaM datasets and TLFs in R for clinical study reports and regulatory submissions

 * Perform independent QC/double programming of SAS and R outputs
 * Build reusable R code for data visualization, exploratory analysis, and statistical summaries
 * Collaborate with biostatisticians and study teams on SAPs, specs, and timelines
 * Support the team's R infrastructure and reproducible programming practices