Site Name: USA – Pennsylvania – Upper Providence, UK – Hertfordshire – Stevenage
Posted Date: Oct 5 2022
US Hiring Locations: Upper Providence, PA
UK Hiring Locations: Stevenage, Hertfordshire
Remote Working: Possible option
Our team collaborates with top laboratory and clinical scientists to advance innovative ideas in drug discovery. We design experiments, analyze data, and visualize results for projects that range from small studies with single endpoints to high-dimensional genomic data. We use traditional statistical methods and modern machine learning algorithms, design experiments to develop new technologies and analyze data to identify biomarkers for clinical trials. Our work is varied and challenging with the common goal to advance the science of human health.
To succeed, team members need good technical and communication skills, the desire to develop their statistical and scientific knowledge continually, and the ability to develop practical solutions and apply statistical techniques in creative ways. Successful candidates will be innovative, pragmatic, and flexible, thriving in a dynamic, collegial environment with frequent new challenges and excellent opportunities to develop and succeed.
In this role, you will provide hands-on statistical consulting for scientific research areas within GSK drug discovery.
Key Responsibilities include, but are not limited to (vary by position level):
- Collaborating with GSK scientists and scientific management to address important drug discovery questions with statistical methods
- Identifying key scientific challenges that can be addressed with statistical methods and proposing how to do so
- Applying existing statistical methods or developing new methods to address scientific problems
- Designing experiments and ensuring they address scientific questions clearly and accurately
- Analyzing data and ensuring the results can be relied upon for making important drug discovery decisions around targets, molecules, and technologies
- Communicating statistical concepts, designs, and analytical results clearly and accurately to GSK scientists and research managers at all levels
- Working with other statisticians on internal department initiatives, e.g., to develop specific technical or consulting skills, streamlined processes, etc.
- Reviewing literature and writing simulations to evaluate statistical methods for application to drug discovery problems.
- Collaborating with other internal statistics teams to accomplish joint objectives.
- Supervising a small team (2-5 people) of statisticians, enhancing their ability to address key scientific questions by providing technical (statistical and scientific) direction to projects and by developing their consulting skills
- Identifying and contributing statistics methodological expertise within the team through ongoing personal development and collaboration on challenging technical problems
GSKs overall R&D strategy focuses on science related to the immune system, the use of human genetics and advanced technologies. These unlock the potential of new areas of science, enabling us to design and develop new classes of medicine and bring them to patients more quickly and cost-effectively.
Applications close once position is filled.
Please take a copy of the Job Description, as this will not be available post closure of the advert.
When applying for this role, please use the cover letter of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.
During the course of your application you will be requested to complete voluntary information which will be used in monitoring the effectiveness of our equality and diversity policies. Your information will be treated as confidential and will not be used in any part of the selection process. If you require a reasonable adjustment to the application / selection process to enable you to demonstrate your ability to perform the job requirements please contact 0808 234 4391. This will help us to understand any modifications we may need to make to support you throughout our selection process.
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#Biostatistics2021
Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:
- MSc or PhD in statistics, biostatistics, or a closely related field with formal statistical training
Preferred Qualifications:
If you have the following characteristics, it would be a plus:
- Strong academic record
- Significant experience as a statistician, collaborating with scientists from other disciplines
- Strong oral and written English communication skills
For Principal Statistician ability to:
- Apply statistical skills accurately to practical problems
- Collaborate well with statisticians and scientists from other disciplines
- Explain novel and standard statistical methods clearly to scientific colleagues
- Identify existing or develop new statistical methods to improve the design, analysis, and interpretation of scientific studies
- Evaluate, recommend, and implement statistical tools for addressing scientific problems
- Learn new statistics skills quickly and independently
For Statistics Leader demonstrated ability to:
- Identify existing or develop new statistical methods to improve the design, analysis, and interpretation of scientific studies in drug discovery
- Evaluate, recommend, and implement statistical tools for addressing scientific problems
- Deliver statistical consulting (design, analysis, and interpretation of studies) to scientists in multiple disciplines
- Take a leadership role in multi-disciplinary teams
- Build and maintain relationships with customer groups
- Drive the adoption of statistical best practice within Research & Development
- Lead initiatives within a statistics team to develop internal capability
- Develop junior staff through mentoring or supervision
- Interest in continually learning and applying new statistical skills
Motivated to continue learning new statistical skills and to solve challenging problems in drug discovery
Practical understanding of at least some of the following statistics topics:
- Experimental design, mixed models, Bayesian methods, linear and nonlinear regression, repeated measures, machine learning algorithms, analysis of high-dimensional data
- Genomics, molecular biology, disease biology, and cellular, tissue, and animal models
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