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BioRenderBioRenderUnited States

Senior Applied Biostatistician (R)

Lead statistical analysis and visualization capabilities for BioRender's Graphing product. Own R implementation, analysis validation, roadmap definition, and cross-functional statistical literacy.

Salary not listed
Remote4+ YOEData Science

About the role

What you'll be doing

  • Own the statistical rigor of the Graphing product by validating analysis correctness, refining input/output accuracy, and ensuring statistical workflows meet trusted scientific standards (e.g., GraphPad Prism)
  • Define "recommended" analyses and sub-analyses for user workflows, including in-product context, explanations, and warnings
  • Partner with product and engineering to shape the stats roadmap: methods to add, interdependencies, R model complexity, and system integration
  • Build and maintain production R code powering statistical features, with robust testing fixtures and QA workflows
  • Level up team statistical literacy by partnering with product, engineering, and design
  • Serve as diagnostic backstop for support escalations from Sales and Customer Success; triage issues and feed insights back into roadmap
  • Leverage AI-assisted tooling to accelerate implementation and iteration
  • Identify AI opportunities for new workflows, automation, or intelligence; partner with engineering and design to implement responsibly
  • Contribute to the broader BioRender Data Science brand and strategy

What you bring

  • Master's or PhD in Biostatistics, Statistics, or closely related quantitative field
  • 4+ years post-academia experience in an analytical or applied statistics role, ideally working closely with product, engineering, and design teams
  • Production-level R proficiency, including package development, testing, and code review
  • Track record of writing code (R, Python, or similar) to implement complex statistical analyses—not just configuring tools or running canned procedures
  • Familiarity with common scientific analysis tools (e.g., GraphPad Prism, SAS, JMP, Stata) and statistical conventions
  • Strong written and verbal communication skills; ability to explain statistical tradeoffs to non-specialists
  • Quick learner who stays current with new methodologies and tooling

Bonus

  • Experience with multivariate analyses (PCA, multiple linear regression), multi-way ANOVA, or pharma/biotech workflows like PK/PD modeling
  • Teaching or research experience in biology-related fields

Skills

RPythonStatistical AnalysisBiostatisticsMultivariate AnalysisAnovaPk/Pd ModelingGraphpad PrismSasJmp

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