Senior Applied Biostatistician (R)

About the role

We're looking for a statistical expert to join our Graphing team at BioRender. Your role will be to ensure the statistical analysis and visualization capabilities in our products meet or exceed trusted scientific standards.

Responsibilities

• Own the statistical rigor of the Graphing product by validating analysis correctness, refining input/output accuracy, and ensuring our statistical workflows meet or exceed trusted scientific standards.
• Define the "recommended" analysis and sub-analyses for each user workflow, including the in-product context, explanations, and warnings that help users understand why a given method fits their data — and when it doesn't.
• Partner with product and engineering to shape the stats roadmap: which methods to add next, how they interrelate, what complexity and infrastructure each new R model requires, and how to bring it into the system as a usable analysis and visualization.
• Build and maintain production R code that powers these statistical features, with robust testing fixtures and QA workflows.
• Level up the team's statistical literacy over time — bring product, engineering, and design along for the ride so SME knowledge compounds rather than staying siloed.
• Be the diagnostic backstop for support escalations from Sales and Customer Success triage whether an issue is a stats service bug, a product app bug, or a user setup problem, and feed insights back into the roadmap.
• Leverage modern AI-assisted tooling pragmatically to accelerate implementation and iteration where appropriate.
• Identify opportunities where AI can unlock new workflows, automation, or intelligence, and partner closely with engineering and design to bring them to life responsibly and pragmatically.
• Contribute to the broader BioRender Data Science brand and strategy.

Requirements

• Master's or PhD in Biostatistics, Statistics, or a closely related quantitative field.
• 4+ years of experience post-academia 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 your own code (R, Python, or similar) to implement complex statistical analyses — not just configuring existing tools or running canned procedures.
• Familiarity with common scientific analysis tools (e.g. GraphPad Prism, SAS, JMP, Stata) and their statistical conventions.
• Strong written and verbal communication skills, with the ability to explain statistical tradeoffs to non-specialists.
• Quick learner who stays current with new methodologies and tooling.

Bonus

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

Qualifications

• Master's or PhD in Biostatistics, Statistics, or a closely related quantitative field.
• 4+ years of experience post-academia 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 your own code (R, Python, or similar) to implement complex statistical analyses — not just configuring existing tools or running canned procedures.
• Familiarity with common scientific analysis tools (e.g. GraphPad Prism, SAS, JMP, Stata) and their statistical conventions.
• Strong written and verbal communication skills, with the ability to explain statistical tradeoffs to non-specialists.
• Quick learner who stays current with new methodologies and tooling.

Skills

• Master's or PhD in Biostatistics, Statistics, or a closely related quantitative field.
• 4+ years of experience post-academia 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 your own code (R, Python, or similar) to implement complex statistical analyses — not just configuring existing tools or running canned procedures.
• Familiarity with common scientific analysis tools (e.g. GraphPad Prism, SAS, JMP, Stata) and their statistical conventions.
• Strong written and verbal communication skills, with the ability to explain statistical tradeoffs to non-specialists.
• Quick learner who stays current with new methodologies and tooling.

Benefits

• Remote-first with team members across Canada and the U.S., offering you the flexibility to work from anywhere.
• Equal Opportunity Employer.

Pay

Competitive salary based on experience and qualifications.

Schedule

Full-time position.