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Statistics Leader
UK Hiring Locations: Stevenage and GSK HQ (Central London)
This is an exciting opportunity to join GSK and channel your passion for Innovation in the field of Statistics and Data Science to help transform the way in which we use data and quantitative thinking to drive decision-making in R&D. We are growing our cutting-edge statistical innovation and data science capabilities by expanding the Statistics & Data Science Innovation Hub (SDS-IH) led by Prof. Nicky Best. SDS-IH is a methodologically focused, solution-oriented functional group within GSK's Biostatistics department. Biostatistics is comprised of Statisticians, Programmers and Data Scientists within GSK R&D, numbering approximately 700 permanent people in the US, UK, Europe and India. Our work ensures that robust quantitative examination and statistical design and analysis is at the heart of R&D decision-making and enables scientists to make timely, data-driven choices about which potential new medicines and vaccines are most promising to add value for patients - ultimately making the development process more efficient and maximising success.
Within the Statistical Innovation (SI) Pillar of SDS-IH, led by Dr Adrian Mander, we have an opening as a real-world data methodologist working for Thomas Drury. The SI team focuses broadly on the development and application of advanced biostatistics methods for clinical trial design and analysis. Active areas of research and support include, but are not limited to, Bayesian dynamic borrowing and other information-borrowing methods, complex innovative study design (e.g., Bayesian and non-Bayesian adaptive trials, master protocols, seamless designs, basket PoC trials), optimal use of the estimands framework, efficient quantitative decision making (e.g., Go/No Go decision making), use of historical data and/or real-world evidence (RWE) for clinical trial design and analysis, and the design of hybrid or externally controlled trials.
Join the Statistics & Data Science Innovation Hub, Statistical Innovation Pillar.
In this role you will
• Develop and implement innovative statistical methodologies to address complex research questions and improve decision-making processes in both clinical and real-world settings.
• Consult with cross-functional teams to understand their statistical and RWE and Epi needs and provide appropriate solutions.
• Provide statistical expertise and guidance to project teams, including the selection of methodology to use and hands on implementation work.
• Stay abreast of the latest developments in statistical methodologies for RWE, and epidemiology, and incorporate these into practice where appropriate.
• Participate in external scientific, regulatory and professional meetings and forums to represent GSK and maintain visibility in the field.
• Support identification, development, and application of novel statistical methodologies to increase efficiency and effectiveness of analyses that involve real-world data.
Why you?
Basic Qualifications & Skills:
We are looking for professionals with these required skills to achieve our goals:
• PhD (or an MSc. with significant work experience and methodology publications) in Statistics, Biostatistics, Epidemiology, or a related field.
• Experience in the application of advanced statistical methods in the pharmaceutical industry or healthcare setting, with a focus on RWE and epidemiology.
• Sound knowledge of Causal Inference and Target Trial Emulation.
• Proficiency in statistical programming languages (e.g., R, SAS, Python).
• Substantial interest in driving both the development of new methodological solutions as well as the identification and application of existing, state-of-the art solutions to meet the needs of GSK's diverse R&D portfolio.
• Superb written and verbal communication skills with a demonstrated ability to influence non-specialists to adopt innovation where necessary for smart risk-taking.
Preferred Qualifications & Skills:
Please note the following skills are not necessary, just preferred, if you do not have them, please still apply:
• Demonstrable evidence of statistical innovation and technical statistical strength, including publication in major scientific journals, conferences, or other scientific proceedings.
• Experienced user of modern biostatistical methods relevant to drug development, such as Bayesian and/or non-Bayesian adaptive trial design, clinical t
Location: Anywhere
Posted: Nov. 10, 2024, 6:22 a.m.
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