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Overview / About us
The Biostatistician executes statistical analyses of patient-centered outcomes (PCO), including patient-reported outcome (PRO) and clinical outcome assessment (COA)-related endpoints, in direct support of the Director, Biostatistics' PRO/COA methodology workstream. Working within the standards, templates, and R-based tooling the Director establishes, this role performs hands-on PRO efficacy analyses (e.g., MMRM, responder analyses, Time to Deterioration), applies the estimand framework and intercurrent event handling consistent with ICH E9(R1), and supports development of compliance- and audit-ready documentation for EU Joint Clinical Assessment (JCA) submissions under Regulation 2021/2282 and related dossiers. This role owns execution of assigned analyses from planning through reporting and translates complex statistical findings into decision-ready outputs for technical and non-technical audiences, partnering directly with Sponsors and internal cross-functional teams to deliver scientifically rigorous work within consulting timelines.
Responsibilities / Position overview PRO/COA Statistical Execution Executes JCA analyses, related PRO analyses, and post-hoc PRO analyses of US trials as directed by the Director, Biostatistics.
Performs PRO efficacy analyses including MMRM, ANCOVA, responder analyses, and Time to Deterioration (TTD), consistent with methodology and standards established by the Director.
Applies multiple imputation and other missing-data methods (e.g., tipping point analysis, pattern mixture modeling, as directed) to address missingness in longitudinal PRO/COA data.
Supports development and application of Minimal Important Difference (MID) thresholds for responder analyses, under Director oversight.
Applies estimand framework principles and intercurrent event handling consistent with ICH E9(R1).
Conducts subgroup and effect-modification analyses to characterize how patient-centered treatment benefit varies across populations and PICOs.
Statistical Strategy Input & Study Design Support
Contributes to fit-for-purpose analytic strategies for PCO under the Director's direction, aligned to study objectives, evidence needs, and stakeholder context.
Articulates key assumptions, tradeoffs, and limitations of assigned analyses to support decision-making under real-world constraints.
Statistical Analysis Planning & Documentation
Prepares clear, reviewable analysis plans and technical documentation (SAP-style methods documents, analysis specifications, output shells) using templates and standards established by the Director, ensuring transparency, reproducibility, and audit readiness.
Contributes documentation aligned to JCA dossier appendix requirements (protocols, SAPs, evidence-synthesis reports, programming code), including JCA Appendix D.3 evidence-synthesis standards.
Methods for Challenging PRO/COA Data
Selects and applies appropriate approaches for skewed, bounded, categorical, and longitudinal PRO/COA data, including missing data handling and sensitivity analyses, consistent with Director-defined methodology.
Trial PRO Endpoint Analysis & Post-hoc Analysis Designs and implements statistical approaches for analyzing PRO/COA endpoints in interventional studies, aligned to protocol objectives and Director-set standards.
Conducts post-hoc analyses of clinical trial data to identify additional treatment benefits or insights related to patient-centered outcomes.
COA/PRO Evidence Packages Authors or contributes to JCA submission dossiers (e.g., PICO-specific summaries) and statistical/quantitative sections of COA regulatory dossiers, under Director review.
Results Interpretation & Reporting
Interprets analytical results and develops clear, decision-ready reports and evidence narratives suitable for both technical and non-technical audiences.
Statistical Programming in R
Develops and executes statistical programming in R using the reusable, functional-programming-based tools and traceable, quality-controlled workflows established by the Director, to deliver reviewable outputs in a collaborative programming environment.
Sponsor Partnership & Consulting Delivery
Partners with Sponsors and internal cross-functional teams as a consultative methodological resource; maintains strong client relationships by delivering scientifically rigorous analyses while staying responsive to timelines, including JCA submission deadlines tied to EMA centralized procedure timing.
Qualifications
Master’s degree or higher in Biostatistics, Statistics, Quantitative Psychology/Psychometrics, or a related quantitative discipline.
3–5 years of experience designing and executing statistical analyses in an applied setting (life sciences consulting, health outcomes research, applied academic/medical research, or similar), including end-to-end delivery from analysis planning through reporting.
Experience analyzing PICOs and PRO/COA endpoints in interventional clinical trials and translating results into stakeholder-relevant evidence.
Demonstrated expertise applying trial-aligned statistical methods for PRO endpoints, as applicable (e.g., MMRM, ANCOVA, logistic regression, responder analyses, non-parametric approaches when appropriate), including missing data handling and sensitivity analyses.
Working knowledge of estimand framework principles and intercurrent event handling consistent with ICH E9(R1).
Working knowledge of the EU HTA Regulation (2021/2282) and JCA process, including PICO scoping methodology and awareness that a single JCA may involve multiple member-state-specific PICOs; familiarity with national HTA body considerations (e.g., IQWiG/G-BA, HAS, NICE) and FDA/EMA PRO guidance a plus.
Proficiency in R for statistical programming, including the ability to apply functional-programming-based tools and own analysis workflows end-to-end (data-to-results-to-reporting) using reproducible, reviewable code.
Experience preparing analysis plans and technical reports using standardized templates to ensure consistency, efficiency, and audit-ready documentation.
Demonstrated ability to communicate modeling decisions, diagnostics, limitations, and implications clearly to non-technical stakeholders.
Experience working in a quality-controlled and collaborative programming environment.
Experience leveraging emerging AI tools to scale statistical programming and enhance scientific writing efficiency while maintaining analytical rigor and documentation quality.
Direct experience contributing to a JCA dossier (e.g., Appendix D.3 evidence synthesis) preferred but not required.