Director - Oncology Genomics, HGG in Stevenage

Company Overview

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.

Job Purpose

Are you looking for an opportunity to lead a Translational Data Science team within Oncology Genomics in GSK’s Research Technology department and aid in the discovery and development of new cancer medicines? If so, this is the job for you. As a Director in Translational Data Science in the Oncology Genomics team you will lead, plan and coordinate computational biology and genomics projects in partnership with functions across GSK including the Oncology Research Units with the aim to discover and develop the next generation of oncology therapeutics. You will work in an inter-disciplinary environment, frequently interfacing with wet‑lab and translational scientists, clinicians, statisticians, and AI/ML colleagues among others.

Key Responsibilities

• Lead and build a growing team of Oncology Computational Biologists and Genomicists to support and innovate the Oncology portfolio pipeline.
• Contribute scientific expertise and design to multiple drug discovery or development efforts across oncology.
• Act as a competent and recognized expert in developing and critiquing the scientific validity of research/development initiatives to drive the development and delivery of long‑term scientific strategy in Oncology Genomics.
• Individually contribute with analyses and integration of complex cancer datasets, including analysis of gene & protein expression (bulk + single cell + spatial), somatic mutations, copy‑number alterations, and structural variants.
• Apply statistical methods and AI/machine‑learning algorithms to identify patterns in data, predict drug response, and discover potential biomarkers.
• Critically evaluate results and conduct survival analysis to assess the impact of various factors on patient outcomes.
• Lead the development and use of bioinformatics pipelines.
• Serve as a recognized leader in driving technological foresight within specific scientific function or directing content of programs.
• Lead and influence the outcome of multidisciplinary meetings including partners in therapeutic research units, translational and clinical development teams.
• Communicate complex scientific findings clearly to both technical and non‑technical audiences.
• Maintain current knowledge of advancements in cancer research and computational biology.
• Effectively communicate findings to appropriate senior GSK internal groups.
• Utilize your track record of effecting substantial change by applying interdisciplinary knowledge of multiple disciplines and therapeutic areas that impact discovery and/or development in oncology.
• Apply scientific skills to influence experimental design and data interpretation that impacts across drug discovery & development.
• Define and execute a coordinated and highly influential scientific strategy.
• Accountable for decisions affecting major product development activities or business directives and their implementation and for recommending allocation of resources with key matrix partners.

Basic Qualifications

• PhD with postdoc or industry experience OR MS with extensive years of related experience in Computational Biology, Bioinformatics, Cancer Biology, or a related field.
• Proven track record of leadership or matrix leadership experience in Computational Biology, Cancer Biology or a related field.
• Strong understanding of cancer biology and the drug discovery process.
• Proficiency in Python or R, with experience building bioinformatic workflows and documenting code with version control.
• Experience working with large‑scale oncology datasets (e.g., TCGA, CPTAC, DepMap, PRISM).
• Understanding of statistical methods, machine learning and/or AI/ML algorithms, and survival analysis techniques.

Preferred Qualifications

• Leadership with line management experience in Data Science in Oncology Research and Development in Industry, Biotech or Academic settings.
• Expertise and experience in integrating translational and real‑world clinical and ‘omics data with preclinical data for target discovery, biomarker and patient selection strategies.
• A strong publication track record and internationally recognized research experience.
• Knowledge of multiple disciplines and therapeutic areas that impact discovery/development policy, processes or guidelines in the pharmaceutical industry.
• Demonstrated ability to coordinate outputs from several expertise areas to determine strategy.
• Proven track record of effecting substantial change.
• Ability to make decisions.
• Expert in integration of preclinical development disciplines and commercial strategy into a full‑scale product development activity.
• Ability to influence others.