# Senior Applied Biostatistician (R)

**Company:** [BioRender](https://hotfix.jobs/companies/biorender)
**Location:** Remote
**Role:** Data Science
**Experience:** 4+ years
**Skills:** R, Python, Statistical Analysis, Biostatistics, Multivariate Analysis, Anova, Pk/Pd Modeling, Graphpad Prism, Sas, Jmp
**Posted:** 2026-05-19

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

## Job Description

## 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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