Statistics Leader

**Site Name**: UK - London - New Oxford Street, Amsterdam, Collegeville TSA, Rockville Biopharm, Siena, Stevenage, Waltham, Wavre
**Posted Date**: Aug 29 2024

At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. R&D is committed to discovering and delivering transformational vaccines and medicines to prevent and change the course of disease. Science and technology are coming together in a way they never have before, and we have strong tech-enabled capabilities that allow us to build a deeper understanding of the patient, human biology and disease mechanisms, and transform medical discovery. We are revolutionising the way we do R&D. We’re uniting science, technology and talent to get ahead of disease together.

Find out more:
Our approach to R&D.

This is an exciting opportunity to channel your passion for Innovation in the field of Statistics and Data Science to help shape the future of the Biostatistics function and transform the way in which GSK uses data and quantitative thinking to drive disease-aligned decision-making in R&D. We are recruiting a group of technically skilled statisticians to focus on enhancing disease-level knowledge for the company’s core strategic focus of oncology, immunology, respiratory, vaccines and infectious diseases. Working within our methodological centre for statistical innovation, and alongside colleagues deployed to project-facing programme and asset teams, you will build on existing work to build ‘disease-drug-trial’ models across the chevron of translational medicine and clinical development.

Biostatistics is the single-largest functional group of Statisticians, Programmers and Data Scientists within GSK R&D across the US, UK, Europe and India. Our mission is to put statistical thinking at the heart of R&D decision-making; to ensure that predictive models and well-designed experiments and trials deliver robust evidence as the input to those decisions - ultimately making the R&D process more efficient and increasing the probability of success. We are investing in our cutting-edge innovation capabilities by expanding the Statistics & Data Science Innovation Hub (SDS-IH) led by Prof Nicky Best. The vision of SDS-IH is to be the catalyst for innovation and advanced data-driven decision making.

**In this role you will**
- _ Enhance our disease understanding through the implementation of advanced statistical and/or machine learning methodologies across a range of areas from complex in-vitro models through to market access activities involving real world data to directly support business critical projects. _
- _Identify opportunities to utilize statistical methods to further enhance our disease understanding. Collaborate with cross functional quantitative groups to help determine the optimal analytical methods using appropriate data sources._
- _ Contribute to planning and lead implementation of small-to-moderate complexity projects within Biostatistics, ensuring they have clear objectives, achievable timelines, intermediate milestones, and well-defined criteria for success _
- _Present statistical principles, methods, study designs, and/or results transparently and precisely to GSK researchers and management across all levels, ensuring appropriate understanding and contributing to better quantitative decision-making across drug development_
- _ Interact with external scientific groups (industry, academia, regulators) and vendors through presentations, publications, and collaborations, in order to contribute to innovation and uptake of novel statistical methodology and tools within GSK and across the pharmaceutical industry._

**_ Why you?_**

Qualifications & Skills:

- _ PhD in Statistics, Biostatistics, or a closely related discipline (with formal statistical training)._
- _ Post-graduate experience in clinical trials research in the pharmaceutical or a related industry and evidence of leading statistical methodology innovation. Individuals with an MS (or equivalent) in Statistics, Biostatistics, or a closely related discipline (with formal statistical training) may be considered provided they have significant post-graduate experience._
- _ Evidence, through publications, of methodological innovation and technical strength in advanced statistical modelling and/or modern machine learning techniques beyond research conducted during graduate studies. _
- _Proficiency in coding languages such as R, SAS, Python._
- _ Proficient in both spoken and written English, with the capability to clearly communicate both new and established statistical methods and results based on those methods to peers without substantial statistical training_

Preferred:

- _ Post graduate work experience in statistical consulting, working alongside researchers from various fields to devise practical solutions in response to other researchers’ scientific questions of interest_
- _ Knowledge of or interest multiple