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Director, Biostatistics

Monte Rosa Therapeutics, Inc, Boston, MA, United States


Overview

The Director of Biostatistics is ahands‑on statistical leaderresponsible for the design, analysis, and interpretation ofPhase 1–Phase 3 clinical trialswith a primary focus oninflammation and oncology indications. This role combines scientific leadership withactive execution and intensive CRO oversight, ensuring high‑quality statistical deliverables across outsourced clinical studies. The Director will work closely with Clinical Development and external partners to drive trial design, analysis strategies, and regulatory‑ready outputs while remaining directly involved in study‑level statistical activities. Responsibilities

Statistical Leadership Lead andpersonally contribute to statistical strategy and executionfor Phase 1–3 clinical studies, including first‑in‑human, dose‑escalation, proof‑of‑concept, and registrational trials in oncology and inflammatory diseases. Provide direct input intotrial design, endpoint selection, sample size justification, interim analyses, and adaptive strategies, particularly for early‑stage development Author, review, and approve: Statistical sections of clinical protocols Statistical Analysis Plans (SAPs) Tables, listings, and figures (TLFs) Clinical Study Reports (CSRs) CRO Oversight & Execution Serve as theprimary statistical point of contact for CROs, providing close, day‑to‑day oversight of outsourced biostatistics and programming activities Actively review CRO deliverables forscientific accuracy, consistency, and regulatory compliance, including datasets, analysis outputs, and reports Ensure CROs adhere to agreed‑upon timelines, quality standards, CDISC/CDASH conventions, and statistical methodologies Lead CRO selection, scope definition, and ongoing performance management for biostatistics and programming services Cross‑Functional & Regulatory Engagement Partner closely with Clinical Development to ensure statistical approaches align with program objectives and clinical strategy Finish Provide statistical expertise fordata monitoring committees, interim analyses, and data review meetings Contribute directly toregulatory submissions, briefing documents, and responses to health authority questions Represent biostatistics in cross‑functional development teams and external regulatory interactions as needed Operational Focus Ensure thetimely production and accuracyof all statistical analyses and integrated reports across assigned studies Maintain consistency of statistical approaches across programs while remaining flexible to study‑specific needs Stay current on evolving statistical methodologies, regulatory expectations, and industry best practices relevant to oncology and inflammation trials Statistical Programming Oversight Direct and mentor statistical programmers to ensure accurate, timely, and compliant production of CDISC-compliant datasets (SDTM/ADaM), tables, listings, and figures (TLFs) for clinical study reports. Translate Statistical Analysis Plans (SAPs) into clear, actionable programming specifications and define data structure requirements for external CRO partners or internal teams. Ensure rigorous quality control (QC) and validation of analysis datasets and statistical outputs to meet FDA/EMA regulatory standards. Collaborate with data management and clinical teams to resolve data issues and ensure consistency between clinical databases and statistical outputs. Develop and implement efficient statistical programming workflows, macros, and best practices to improve productivity and compliance across multiple clinical trials Qualifications

PhD in Biostatistics, Statistics, Mathematics, Computer Science, or related field 15 +years of experience supporting clinical drug development, including Phase 1–Phase 3 trials and regulatory submissions Demonstrated experience working inCRO‑heavy models, with direct responsibility for reviewing and managing outsourced statistical work Strong expertise in clinical trial statistics, regulatory standards (FDA, ICH), and industry best practices Proficiency with SAS and other commonly used statistical software

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