Principal Statistical Methodologist, Raleigh, NC

Make your mark for patients

We are looking for a Principal Statistical Methodologist who is curious, collaborative, and strategic to join our Statistical Innovation team within Biometric and Data Sciences (BDS), based in our Raleigh, NC (US) offices.

About the role

As a Principal Statistical Methodologist, you will help shape how evidence is generated, modeled, and communicated across the drug development lifecycle, bringing modern computational and machine-learning methods to bear on real R&D decisions. You will develop and apply advanced data-driven and model-based approaches-drawing on statistics, machine learning, and AI-translate them into robust, reusable tools, and partner across functions to put them to work where they impact drug development decision-making. You will also contribute to the group's scientific profile through publications and external collaboration.

Who you will work with

You will be working in a team that provides statistical consultancy across therapy areas and development stages, partnering closely with colleagues in clinical development, regulatory strategy, data science, and medical affairs. The team values curiosity and problem-solving, practical innovation, clear communication, and collaboration, bringing novel quantitative and computational approaches into real study decisions and sharing learnings with the wider scientific community.

What you will do

• Develop and apply advanced computational and statistical methods, including machine learning, AI, and scenario evaluation using modern simulation approaches, to inform design, analysis, and decision-making across development.
• Build robust, well-engineered, reusable tools and workflows that bring these methods into routine use, with attention to reproducibility and software quality.
• Bring a quantitative lens with appropriate rigor to emerging problems such as synthetic and external control data, causal inference, and digital-twin or simulation-based approaches.
• Partner with statisticians and cross-functional colleagues to identify where computational and data-driven methods add the most leverage and translate complex approaches into clear insight for technical and non-technical audiences.
• Contribute to internal capability building by sharing tools, code, and methods across the team and wider organization.
• Contribute to the group's external profile through scientific publications, conference presentations, and participation in cross-industry initiatives and working groups.

Interested? For this role we're looking for the following education, experience and skills Minimum qualifications

• Doctoral degree in statistics, biostatistics, mathematics, computer science with a strong quantitative/statistical component, or a closely related discipline with a solid grounding in statistical inference and uncertainty.
• Minimum of 3 years of experience within the pharmaceutical industry.

Preferred qualifications

• Experience in advanced computational methodology for clinical development (early to late stage) is an advantage. Direct entry may be considered.
• Strong, multi-language scientific programming skills (R and Python preferred; software-engineering practices such as version control, testing, and reproducible workflows a clear advantage).
• Demonstrated expertise in machine learning and/or AI methods, with hands-on experience applying them to real problems; experience with large language models, causal inference, synthetic data, or digital twin/simulation approaches is a strong advantage.
• 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.
• Clear written and spoken communication in English, including the ability to explain technical concepts to non-technical audiences.

Internal applicants should be in their current job for at least 12 months, must meet performance standards and are not on formal corrective/disciplinary process (PIP), warning, final warning, or compliance warning letters within the last 12 months. Please inform your Manager or your Talent Partner before applying to any internal job opportunities.

Unless explicitly stated in the description, this role is hybrid with 40% of your time spent in the office, regardless of your current contractual agreement. If your current working arrangements differ, please contact your Talent Partner to discuss before submitting your application.

UCB is an equal opportunity employer. All employment decisions will be made without regard to any characteristic protected by applicable federal, state, or local law. UCB invites you to voluntarily self-identify during the application process. Provision of self-identification information is entirely voluntary and a decision to provide or not provide such information will not have any effect on your application for employment, your employment with UCB, or otherwise subject you to any adverse treatment. Any information you provide will be considered confidential and will be kept separate from your application and/or personnel file and will only be used in accordance with applicable laws, orders, and regulations.

Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us on US-Reasonable_Accommodation@ucb.com for application to US based roles. Please note should your enquiry not relate to adjustments; we will not be able to support you through this channel.

Requisition ID: 93379

Recruiter: Kelly Dickinson

Hiring Manager: Baldur Magnusson

Talent Partner: Natacha Tassier

Job Level: MM II

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