DefinedTalent

Senior Biostatistician

Quantitative Biology & BiostatisticsConfirmed live in the last 24 hours

Full-timePrinceton, NJ, USAHybrid

About the Job

Requirements

Substantial hands-on experience as a trial statistician in clinical development, an advanced degree in a quantitative field, and the independence to reason through design, endpoints, estimands, methods, missing data, sensitivity analyses, and interpretation.
Personal authorship of major statistical deliverables, including Statistical Analysis Plans, analysis specifications, TLF shells, and related documentation, plus a working understanding of how the protocol, Statistical Analysis Plan, analysis datasets, specifications, and final outputs connect. Reviewing or approving others’ work does not substitute for authorship.
A skeptical, critical mindset, with the ability to question assumptions, follow up on inconsistencies, examine outputs closely, recognize statistically implausible results, and validate code, software output, and AI-generated work rather than trusting it simply because it ran.
Comfort using SAS and/or R with modern AI-assisted development tools, and the statistical judgment to inspect, modify, debug, and validate results. AI fluency is required; machine learning engineering or AI architecture is not the target.
Practical working knowledge of CDISC, especially ADaM, plus familiarity with SDTM and the broader clinical data and statistical programming workflow.
A solid grasp of FDA and EMA expectations for statistical analyses and deliverables; personal submission leadership is not required.
High autonomy and a practical, proactive approach to investigating unfamiliar statistical, data, or technical problems and working toward solutions.
Clear communication with engineers, clinical teams, and client stakeholders, and the ability to move between methodology, specifications, data, outputs, and AI tooling.

Responsibilities

Write core statistical deliverables for Phase I–III trials, including Statistical Analysis Plans, analysis specifications, TLF shells, and documentation that takes a study from protocol to final outputs.
Own decisions on trial design, endpoints, estimands, analysis methods, missing data, and sensitivity analyses, and justify them against regulatory expectations.
Review analysis datasets, specifications, outputs, and code, including AI-generated work, for statistical soundness, consistency, and traceability before release.
Use generative AI and coding agents daily to write and modify SAS or R code, explore unfamiliar problems, debug, and iterate to working analyses, while remaining accountable for correct implementation.
Partner closely with AI and software engineers to translate statistical intent into product behavior and stress-test model and pipeline outputs, working across SDTM, ADaM, and TLF production.
Apply frontline statistical judgment to the platform by using it on live clinical programs.

Desired Qualifications

Exposure to NDA/BLA submissions or direct interaction with the FDA or other health authorities.
Experience building, specifying, or shaping statistical software, tools, or automation.
Experience in a startup or small, fast-moving team where the problem defines the scope rather than the job title.

Senior Biostatistician

DefinedTalent · Princeton, United States (Hybrid) · Full-time · Posted 2026-10-19

Workplace: hybrid

Department: Information Technology

Description

DefinedTalent is looking for a Sr. Biostatistician to join one of their clients that is transforming clinical data workflows with multi agent ai and automation; cutting cycle times, reducing cost and ensuring compliance. This is a senior individual-contributor role. You’ll own the statistical thinking on trials from start to finish, covering design, endpoints, specifications, outputs, and interpretation. You’ll write the deliverables yourself rather than review work others produce.

Generative AI and coding agents are part of daily statistical work here, and your judgment decides whether the resulting analyses are correct. Instead of a traditional clinical matrix, you’ll work mostly with our AI and software engineers, applying our AI-driven biostatistics platform to real clinical programs.

Responsibilities:
Write the core statistical deliverables for Phase I–III trials, including Statistical Analysis Plans, analysis specifications, TLF shells, and the documentation that takes a study from protocol to final outputs

Own decisions on design, endpoints, estimands, analysis methods, missing data, and sensitivity analyses, and justify them against regulatory expectations

Review analysis datasets, specifications, outputs, and code, including AI-generated work, for statistical soundness, consistency, and traceability before release

Use generative AI and coding agents every day to write and modify SAS or R code, explore unfamiliar problems, debug, and iterate to working analyses, while staying accountable for the correctness of the implementation

Partner closely with AI and software engineers to turn statistical intent into product behavior and stress-test what models and pipelines produce, working across SDTM, ADaM, and TLF production rather than in a statistics silo

Apply frontline statistical judgment to our platform by using it on live clinical programs

Requirements

Substantial hands-on experience as a trial statistician in clinical development, an advanced degree in a quantitative field, and the independence to reason through design, endpoints, estimands, methods, missing data, sensitivity analyses, and interpretation
Must-have: personal authorship of major statistical deliverables (SAPs, analysis specifications, TLF shells, and related documentation), plus a working understanding of how the protocol, SAP, analysis datasets, specifications, and final outputs connect. Reviewing or approving others’ work does not substitute for this.
A skeptical, critical mindset. You question assumptions, follow up on inconsistencies, examine outputs closely, and notice when a result doesn’t make statistical sense. You don’t trust code, software output, or AI-generated work just because it ran.
Comfort with SAS and/or R using modern AI-assisted development tools, and the statistical judgment to inspect, modify, debug, and validate the results. AI fluency is required here. We are not looking for an ML engineer or AI architect.
Practical working knowledge of CDISC, especially ADaM, plus familiarity with SDTM and the broader clinical data and statistical programming workflow
A solid grasp of FDA and EMA expectations for statistical analyses and deliverables. We value this more than having personally led a submission.
High autonomy and a can-do attitude. When you hit an unfamiliar statistical, data, or technical problem, you investigate it, form a view, and work toward a practical solution instead of passing it off.
Clear communication with engineers, clinical teams, and client stakeholders, and the ability to move easily between methodology, specifications, data, outputs, and AI tooling

Nice to Have

Exposure to NDA/BLA submissions or direct interaction with the FDA or other health authorities
Experience building, specifying, or shaping statistical software, tools, or automation
Experience in a startup or small, fast-moving team where the problem defines the scope, not the job title

Benefits

Help redefine how biostatistics and clinical trial delivery work through AI
Work with experienced scientists and engineers from leading pharma and top tech companies, with broad scope and real autonomy over how the statistics get done
Directly shape our core product and client delivery during a period of rapid growth
Competitive compensation and equity, plus comprehensive benefits
Comprehensive health insurance (medical, dental, vision)
401(k) retirement plan with company contribution
Generous paid time off and holidays
Opportunities for rapid professional growth in a high-impact, scaling organization
Collaborative, flat organizational culture with direct access to leadership
Professional development and training support

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About the Company

DefinedTalent

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