Platform Engineer, Statistical Computing (R)

Develop the long-term vision and roadmap for Artera’s statistical computing platform, enabling scalable and reproducible R-based workflows

Build and maintain R-based analytical environments for clinical and outcomes research

Design and operate R package infrastructure, including internal packages, dependency management, and package repositories

Build and evolve core libraries and tooling used by biostatisticians for analysis, reporting, and model validation

Partner with biostatisticians to productionize statistical methods and pipelines

Enable reproducible workflows through containerization, environment management, and versioning (e.g., renv, Docker)

Integrate statistical workflows into Artera’s broader data and AI platform ecosystem

Optimize compute, storage, and data access for large-scale clinical and real-world datasets

Ensure systems meet standards for auditability, reproducibility, and compliance

5+ years of industry experience in software engineering, data engineering, or scientific computing

3+ years of hands-on experience with R programming in production or research environments

Experience developing and maintaining R packages and shared libraries

Experience building or supporting data platforms, scientific computing environments, or analytical infrastructure

Experience with cloud platforms (AWS, GCP, or Azure)

Experience with containerization and reproducible environments (Docker, Kubernetes, etc.)

Strong proficiency in R ecosystem tools (e.g., tidyverse, renv, devtools, pak, shiny app)

Deep understanding of package management, dependency resolution, and reproducibility

Ability to design and build scalable systems for analytical workloads

Strong collaboration skills and ability to work closely with biostatistics and data science teams

Solid software engineering fundamentals (version control, testing, CI/CD)