Principal/Sr Principal Scientist - Applied Genetics
Listed on 2026-02-10
-
Healthcare
Data Scientist -
Research/Development
Research Scientist, Data Scientist
Site Name: USA - Pennsylvania - Upper Providence, Cambridge 300 Technology Square, UK - Hertfordshire - Stevenage
Posted Date: Feb 6 2026
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. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people’s lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients’ needs and have the highest probability of success.
We’re uniting science, technology, and talent to get ahead of disease together.
Find out more:
Our approach to R&D
Position Summary
We are seeking a talented and motivated individual to join our team as a Principal Scientist/Senior Principal Scientist in Applied Genetics within the R&D Translational Sciences team. The R&D Translational Sciences group generates and applies human genetics, genomics, and biomarker insights into key GSK disease areas and product strategies. The successful candidate will have experience in human genetics, statistical genetics, genetic epidemiology, or a related discipline with high computational skills, and will be excited to apply their expertise in human genetics to the development of new medicines.
The Principal Scientist/Senior Principal Scientist will be responsible for performing human genetics & statistical genetics analyses in key disease areas, evaluating genetic evidence and causal biology in support of therapeutic target hypotheses, evaluating and implementing of new analytical methods, and effectively communicating their results and interpretation to peers and leaders. They will have experience working in multi-disciplinary teams to answer complex scientific questions.
This role will provide YOU the opportunity to lead key activities to progress YOUR career.
Key Responsibilities
In this role, you will:
- Apply expertise in human genetics, statistical genetics, genetic epidemiology, or a related discipline to support the development of new medicines.
- Contribute to the ongoing development and iteration of scaled and automated genetic assessment tools to support the advancing science of drug target identification and validation.
- Develop and/or critically evaluate new methods to derive and apply genetic insights to support the development of therapeutic target hypotheses.
- Perform and apply at-scale and bespoke computational and statistical analyses (e.g., GWAS, WGS, Mendelian Randomization, rare variant association testing, and variant to gene mapping) and implement new analytical methods to infer molecular mechanisms to elucidate and interrogate therapeutic hypotheses
- Evaluate genetic and causal biology evidence to support therapeutic target hypotheses and provide clear and concise communication of results and interpretation to peers and leaders.
- Collaborate effectively in multi-disciplinary teams (internal and external) to answer complex scientific questions.
- Identify and implement creative solutions to address challenging scientific questions.
Why You?
Basic Qualifications
- Ph.D in human genetics, statistical genetics, genetic epidemiology, or related disciplines with strong computational and quantitative focus.
- Experience in development, critical evaluation and application of analyses methods to answer complex scientific questions
- Experience in performing analyses and the interpretation of findings of large-scale population based genetic studies (e.g., GWAS and WES/WGS approaches, MR and variant to gene mapping)
- Experience evaluating and integrating genetic and genomic data to evaluate strength of causal genetic evidence (e.g., QTL mapping & integration, causal inference, pathway enrichment)
- Proficient in programming/scripting in R or Python and working within cloud-based computing platforms (e.g., AWS and/or Google Cloud)
- Experience in working with genetics databases and resources including key biobanks and disease-specific consortia data sources
Preferred Qualifications
- Experience…
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