Principal Statistical Methodologist

UCB•Raleigh, NC

8d•Hybrid

About The Position

This role is for a Principal Statistical Methodologist within the Statistical Innovation team in Biometric and Data Sciences (BDS). The position is based in Raleigh, US. The individual will contribute to shaping evidence generation and communication throughout the drug development lifecycle, from early clinical development to regulatory approval and lifecycle management. Key responsibilities include providing expert statistical consultation on trial design and analysis, developing and applying advanced statistical methods, and translating complex quantitative concepts into clear insights for cross-functional partners. The role also involves contributing to scientific communications and external collaborations through publications and industry initiatives.

Requirements

Doctoral degree in statistics, mathematics, or a closely related scientific discipline.
3+ years of experience working in biostatistics within the pharmaceutical industry.
Strong statistical programming skills (R preferred; equivalent tools considered).
Sound knowledge of ICH guidelines and understanding of regulatory requirements from major health authorities.
Ability to work effectively with autonomy, manage multiple priorities, and deliver timely, high-quality outputs.

Nice To Haves

Experience in statistical methodology for clinical development (early to late stage) is an advantage.
Expertise in advanced statistical methods and innovative trial design; experience with causal inference and estimands is an advantage.

Responsibilities

Provide statistical consultation on clinical trial design and analysis across multiple development stages and therapy areas.
Develop and implement innovative statistical approaches, including model-based methods using frequentist and Bayesian techniques.
Run or guide advanced analyses and simulations to inform design options, sample size, and power trade-offs.
Communicate complex quantitative topics clearly using visuals, simulations, and plain language for diverse audiences.
Contribute to internal learning by delivering training on advanced statistical concepts for non-statisticians and statisticians.
Contribute to the group’s external profile through scientific publications, conference presentations, and participation in cross-industry initiatives and working groups.