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
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