Senior Statistician, Early Development

Roche•South San Francisco, CA

About The Position

This role is in Early Development Biometrics (EDB), a core function within Product Development Data Sciences (PDD) that provides strategic leadership and scientific rigor across early clinical development at Roche. We partner across Biostatistics, Analytical Data Science, and Data Management to enable data-driven decision-making from first-in-human through proof-of-concept studies. As trusted partners in early development, we design efficient and innovative clinical trials, apply rigorous statistical methods, and implement high-quality programming and analytical solutions to accelerate timelines, de-risk development, and increase the probability of technical success. Our integrated teams operate with agility and scientific depth, supporting exploratory analyses, early regulatory engagements, and complex data-generation needs across therapeutic areas. Together, we bring scientific rigor, technical innovation, and strategic insight to shape the future of early development and deliver better outcomes for patients. Early Development Biometrics is also home to Methods Collaboration & Outreach (MCO), which enables the most impactful use of quantitative methodology across PDD through internal consultation, external collaboration, and continuous capability building; and Visual Analytics, which creates and maintains interactive dashboards that drive high-quality Medical Data Review (MDR) and safety signal detection, aligned with Risk-Based Quality Management (RBQM) principles and Critical-to-Quality (CtQ) endpoints. The Opportunity The Early Development Statistician is a critical partner in the design and analysis of exploratory clinical studies, applying statistical expertise to guide early-phase trial strategy, design, and interpretation. This role ensures scientific rigor while maintaining the flexibility needed for hypothesis generation and signal detection. Responsibilities include contributing to protocol design, developing statistical analysis plans, and analyzing complex, often high-dimensional data to inform early go/no-go decisions and regulatory interactions. The Statistician helps shape the early clinical narrative by ensuring data are robust, interpretable, and aligned with the evolving development strategy. You independently lead statistical input into early phase clinical trial designs, ensuring alignment with scientific and translational objectives, for example first in human, dose escalation, proof of concept, or biomarker enriched studies, and you utilize innovative or adaptive methodologies where appropriate You own the development and quality review of statistical deliverables including protocols, SAPs, and CRFs, with a focus on fit for purpose design that supports regulatory and internal decision making You design and execute complex analyses, often involving PK PD modeling, exploratory biomarker data, or interim futility assessments, and you proactively identify potential data limitations or methodological challenges and implement solutions You collaborate with study teams to align study timelines and deliverables, bringing a proactive mindset to evolving scientific priorities You interpret and communicate results in context, clearly framing the clinical relevance and implications of early signals to influence go no go decisions, dose or regimen selection, and future trial design You lead statistical contributions to CSRs and regulatory documents, for example IND updates and briefing packages, supporting early regulatory interactions and communications with internal governance bodies Who You Are: You hold an MSc or PhD in Statistics, Biostatistics, or a closely related quantitative field You bring at least 3 years of relevant experience in clinical trial statistics in pharmaceutical, biotech, or CRO settings You have demonstrated experience contributing to the design, analysis, and interpretation of clinical studies across different phases You have a solid understanding of regulatory expectations and statistical methodologies for clinical development You are proficient in SAS and or R and familiar with CDISC standards You work autonomously and collaborate effectively in cross functional teams You demonstrate independent thinking and make decisions based on sound principles You demonstrate excellent strategic agility including problem solving and critical thinking, with agility that extends beyond the technical domain You demonstrate respect for cultural differences when interacting with colleagues in the global workplace You have excellent verbal and written communication skills in presentation and writing, with the ability to explain complex technical concepts in clear language

Requirements

MSc or PhD in Statistics, Biostatistics, or a closely related quantitative field
at least 3 years of relevant experience in clinical trial statistics in pharmaceutical, biotech, or CRO settings
demonstrated experience contributing to the design, analysis, and interpretation of clinical studies across different phases
solid understanding of regulatory expectations and statistical methodologies for clinical development
proficient in SAS and or R and familiar with CDISC standards
work autonomously and collaborate effectively in cross functional teams
demonstrate independent thinking and make decisions based on sound principles
demonstrate excellent strategic agility including problem solving and critical thinking, with agility that extends beyond the technical domain
demonstrate respect for cultural differences when interacting with colleagues in the global workplace
excellent verbal and written communication skills in presentation and writing, with the ability to explain complex technical concepts in clear language

Nice To Haves

Proven experience working in cross-functional, global early development teams, including collaboration with Clinical Pharmacology, Translational Science, and Early Clinical Development functions.
Strong communication skills, with the ability to distill complex, exploratory, or model-based statistical methodologies into actionable insights for clinicians, program leads, and non-statistical stakeholders.
Direct experience supporting early-stage drug development (e.g., Phase I/II trials), with an understanding of the unique design and analysis needs of FIH, SAD/MAD, dose-finding, and proof-of-concept studies.
Ability to influence cross-functional decisions through clear articulation of data implications, and translate preliminary data into strategic development recommendations.
Demonstrated mentoring or leadership experience, particularly in guiding less experienced statisticians or cross-functional partners in early-phase strategy or methodology.
Familiarity with innovative statistical designs, such as adaptive trials, Bayesian frameworks, or model-informed drug development (MIDD), and their application in early clinical research.

Responsibilities

contributing to protocol design
developing statistical analysis plans
analyzing complex, often high-dimensional data to inform early go/no-go decisions and regulatory interactions
independently lead statistical input into early phase clinical trial designs, ensuring alignment with scientific and translational objectives, for example first in human, dose escalation, proof of concept, or biomarker enriched studies, and you utilize innovative or adaptive methodologies where appropriate
own the development and quality review of statistical deliverables including protocols, SAPs, and CRFs, with a focus on fit for purpose design that supports regulatory and internal decision making
design and execute complex analyses, often involving PK PD modeling, exploratory biomarker data, or interim futility assessments, and you proactively identify potential data limitations or methodological challenges and implement solutions
collaborate with study teams to align study timelines and deliverables, bringing a proactive mindset to evolving scientific priorities
interpret and communicate results in context, clearly framing the clinical relevance and implications of early signals to influence go no go decisions, dose or regimen selection, and future trial design
lead statistical contributions to CSRs and regulatory documents, for example IND updates and briefing packages, supporting early regulatory interactions and communications with internal governance bodies
provide functional guidance and informal mentoring, supporting the development of less experienced colleagues in statistical techniques and the strategic application of methods in early phase settings
lead or influence study level projects and contribute significantly to cross study initiatives, for example platform protocols and disease area strategies, driving consistency and innovation across early development programs