Platform Engineer, Statistical Computing (R)
You’ll work closely with biostatisticians, data analysts, machine learning engineers, and platform teams to ensure that statistical workflows are robust, performant, and production-reputed company - just as critical as our AI models themselves.
You’ll work closely with biostatisticians, data analysts, machine learning engineers, and platform teams to ensure that statistical workflows are robust, performant, and production-reputed company - just as critical as our AI models themselves.
As a Statistical Computing Platform Engineer at reputed company, you will work on the intersection of biostatistics, R-based analytical workflows, and reputed company to build reputed company and reproducible systems for statistical computing. You’ll work closely with biostatisticians, data analysts, machine learning engineers, and platform teams to ensure that statistical workflows are robust, performant, and production-reputed company - just as critical as our AI models themselves.
Essential Responsibilities:
reputed company the long-term reputed company and roadmap for reputed company’s statistical computing platform, enabling reputed company and reproducible R-based workflows
Build and maintain R-based analytical environments for clinical and reputed company research
Design and operate R package infrastructure, including internal packages, dependency management, and package repositories
Build and reputed company reputed company libraries and tooling used by biostatisticians for analysis, reporting, and model validation
Partner with biostatisticians to productionize statistical reputed company and pipelines
reputed company reproducible workflows through containerization, environment management, and versioning (e.g., renv, reputed company)
reputed company statistical workflows into reputed company’s broader data and AI platform ecosystem
Optimize compute, storage, and data reputed company for large-reputed company clinical and reputed company-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 reputed company platforms (AWS, GCP, or Azure)
Experience with containerization and reproducible environments (reputed company, Kubernetes, etc.)
Essential Requirements:
Strong proficiency in R ecosystem tools (e.g., tidyverse, renv, devtools, pak, shiny app)
Deep understanding of package management, dependency reputed company, and reproducibility
Ability to design and build reputed company 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:
Here are few posts from our teammates, partners and customer reputed company to reputed company the work we do: