Principal Statistician, Real-World Biostatistics

GSK; Camden Town; On-site; GBP 55,000 - 75,000; Full time

Job summary

A global healthcare company is looking for a Project Biostatistician to lead the analysis of non-interventional studies. The ideal candidate will have a PhD or Master's in Statistics/Data Science with 3+ years' experience in the pharmaceutical industry. Strong skills in statistical analysis and RWD expertise are essential. This role involves collaboration with cross-functional teams and presenting findings to stakeholders. The position is based in Camden Town, UK.

Qualifications

• PhD with 3+ years or Master's with 5+ years of relevant industry experience.
• Experience with RWD and applying biostatistical principles in research.
• Advanced skills in statistical analysis methods.

Responsibilities

• Lead design and analysis of non-interventional studies.
• Collaborate with teams to ensure quality control.
• Present insights effectively to stakeholders.

Skills

Statistical analysis

RWD expertise

Communication

Project management

Programming in R and SQL

Education

PhD or Master's degree in Statistics, Data Science, Epidemiology

Tools

Statistical software (R, SQL)

Job description

Overview

Biostatistics:

• As a Project Biostatistician, lead the design and analysis of non-interventional studies, aligning with cross functional teams, managing timelines, and ensuring methodological rigor and quality control.
• Apply statistical and RWD expertise to guide the selection and appropriate use of complex health data sets, co-develop variable definitions, code lists, and author technical specification documents.
• Develop and refine statistical analysis plans, conduct complex statistical analyses, including for example causal inference, comparative effectiveness, target trial emulation, and communicate findings to internal and external stakeholders.

Responsibilities

• Serve as an RWB consultant within matrix teams, leveraging in-depth expertise on assigned assets.
• Serve on enterprise level strategic initiatives, for example Disease Area Acceleration Teams, for organizational deliverables.
• Present statistical analyses and insights effectively to internal stakeholders and external audiences, including conferences and publications, showcasing the value of biostatistical contributions.
• Engage in strategic communication to reinforce the role of biostatistics in driving innovation and decision-making across the organization.
• Stay informed on emerging industry trends and incorporate cutting-edge biostatistical methods to improve study designs and analytics.
• Conduct methodological research and contribute to the development/application of new analytical techniques.
• Provide biostatistical expertise on RWD during regulatory submissions, preparing for meetings and addressing regulatory queries to ensure compliance with industry standards.
• Stay current with regulatory guidance on the use of RWD for decision-making and advise on statistical approaches aligned with regulatory expectations.

Qualifications

• PhD or Master's degree in Statistics, Data Science, Epidemiology, or related field.
• PhD with 3+ years work experience / Master's degree with 5+ years in the pharmaceutical/biotech industry, preferably in real-world evidence, epidemiology, or health outcomes research.
• Experience working with drug development processes utilizing statistical skills to achieve project and business objectives.
• Experience using RWD (e.g., electronic health records, insurance claims, registries) and applying observational study designs and biostatistical principles in clinical/epidemiological research.
• Experience in programming languages R and SQL, working with observational datasets.
• Experience contributing to methodological research and publications in the field of biostatistics and real-world data analytics.

Preferred Qualifications

• Experience working within regulatory frameworks related to RWD.
• Experience in advanced biostatistical techniques, including causal inference, comparative effectiveness, time to event analysis, longitudinal and predictive modelling, and external control arms.
• Familiarity with machine learning techniques and applications in real-world data analysis.
• Demonstrated ability to manage complex projects and deliver high-quality results in dynamic environments.
• Strong communication and interpersonal skills to effectively convey complex statistical concepts.
• Fluency in written and spoken English.