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MSD - Postdoctoral Research Fellow Statistics

About the role

3-year Fixed-Term

We are a research-driven biopharmaceutical company. Our mission is built on the simple premise that if we “follow the science” and that great medicines can make a significant impact to our world. And we believe that a research-driven enterprise dedicated to world-class science can succeed by inventing medicine and vaccine innovations that make a difference for patients across the globe.

You will be part of the BARDS organization which has a presence in the US, Europe and Asia Pacific. By joining our company, in this role you will apply your skills and experience in support of developing scientifically based arguments aiming to provide fair accessibility to drugs and vaccines making a real difference in patient’s lives.

The Biostatistics and Research Decision Sciences (BARDS) organization has a proud record of providing comprehensive analytical and methodological expertise to support our company’s strategic goals. Our quantitative scientists aspire to maintain the highest quality output while adopting the most efficient and effective scientific and operational procedures that will promote breakthrough innovation, collaboration and professional activity.

We are currently looking for a Postdoctoral Research Fellow, Statistics (full-time, 3-year fixed-term) to join the team based in our office in London, United Kingdom.

As a postdoctoral research fellow in BARDS, you will work with a highly collaborative team of quantitative scientists to design and execute patient preference research and incorporate preference weights and clinical trial outcomes for drug or biologic into statistical models for quantitative benefit-risk (BR) analysis. Novel data driven approaches will be used to better understand the BR profiles of target subpopulations to deliver improved treatment strategies.

Key Responsibilities:

Assess patient preference research landscape to inform weighting of benefits and risks for quantitative benefit-risk profile.
Based on real clinical trial data, carry out simulations as needed to address realistic scenarios/issues identified as relevant for BR subgroup analysis.
Develop expertise in developing a structured BR framework and quantitative BR methodologies (e.g., Multi-Criteria Decision Analysis [MCDA]) to address multiple and potentially conflicting criteria, differing perspectives, and uncertainty.
Develop expertise in statistical learning (e.g., clustering and Principal Component Analysis) to identify patient characteristics to treatment response.
Develop expertise in visual analytics to develop appropriate visual/graphical displays to support interpretation and aid decision-making.
Develop and maintain good working relationships with internal and external experts in the field.
Deliver high-quality peer review publications and present research results to internal and external audiences.

Your Profile

Education and Minimum Requirement:

PhD in biostatistics, quantitative epidemiology, mathematics, or any other scientific disciplines with substantial quantitative statistics elements. You must have completed your PhD no longer than six months before the starting date.

Required Skills and Experience:

Fluency in English (oral and written).
Skilled in statistical modeling and data simulations
Experience and willingness to work in a global cross-functional team.
Strong leadership, problem solving and trouble-shooting skills.
Proven ability to complete research projects, as evidenced by peer-reviewed publications and conference presentations.
Ability to independently design experiments, interpret data, and incorporate data into statistical models.
Excellent oral and written communication skills
Must also demonstrate the ability to learn, be proactive and motivated, and consistently focus on details and execution.

Preferred Skills and Experience:

Experience in preference research, statistical machine learning and/or quantitative BR assessments in clinical research environment a plus.
Demonstrated experience leveraging gen AI tools to enhance daily workflows and support coding tasks
Understanding of biology of disease and drug development.
Publication record in peer reviewed statistical/medical journals