Platform Engineer, Statistical Computing (R)
Artera›
📍US
Posted 3d ago · via lever
Apply on lever→Job Description
You’ll work closely with biostatisticians, data analysts, machine learning engineers, and platform teams to ensure that statistical workflows are robust, performant, and production-ready - just as critical as our AI models themselves.
Essential Responsibilities:
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
Experience Requirements:
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.)
Essential Requirements:
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)
Work Authorization Requirement:
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Details
- Department
- Tech
- Work Type
- remote
- Locations
- US
- Posted
- April 12, 2026
- Source
- lever