Company OverviewAt 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.GSK has kicked off 2025 with impressive growth in sales, profits, and earnings. We anticipate five major new FDA product approvals and 15 phase III/pivotal study readouts over the next two years. So far, we have secured two FDA approvals, with three more expected later this year. By uniting science, technology, and talent, we are committed to getting ahead of disease together.Job PurposeAre 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.GSK’s Oncology portfolio has seen significant growth in the past years. In the late-stage setting, we have seen numerous approvals and positive Phase 3 readouts. We also have several early-stage programs aiming to enter the clinic over the years to come. Oncology is now posed to be a significant growth driver for GSK, allowing us to be ambitious for patients and continue investment into early drug discovery. To achieve these aims requires leadership in computational biology to derive decision making insights from complex oncology genetic and genomic datasets.Key ResponsibilitiesLead and build a growing team of Oncology Computational Biologists and Genomicists to support and innovate the Oncology portfolio pipelineContribute scientific expertise and design to multiple drug discovery or development efforts across oncologyAct 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 GenomicsIndividually contribute with analyses and integration of complex cancer datasets. This includes analysis of gene & protein expression (bulk + single cell + spatial), somatic mutations, copy number alterations, and structural variantsApply statistical methods and AI/machine learning algorithms to identify patterns in data, predict drug response, and discover potential biomarkers. Critically evaluate results. Conduct survival analysis to assess the impact of various factors on patient outcomesLead the development and use of bioinformatics pipelinesServe as a recognized leader in driving technological foresight within specific scientific function or directing content of programsLead 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 groupsUtilize your track record of effecting substantial change by applying interdisciplinary knowledge of multiple disciplines and therapeutic areas that impact discovery and/or development in oncologyApply scientific skills to influence experimental design and data interpretation that impacts across drug discovery/developmentDefine and execute a coordinated and highly influential scientific strategyAccountable for decisions affecting major product development activities or business directives and their implementation and for recommending allocation of resources with key matrix partnersBasic QualificationsPhD 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 fieldStrong 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 AIML algorithms, and survival analysis techniques.Preferred QualificationsLeadership with line management experience in Data Science in Oncology Research and Development in Industry, Biotech or Academic settingsExpertise and experience in integrating translational and real-world clinical and ‘omics data with preclinical data for target discovery, biomarker and patient selection strategiesA strong publication track record and internationally recognized research experienceKnowledge of multiple disciplines and therapeutic areas that impact discovery/ development policy, processes or guidelines in the pharmaceutical industryDemonstrated ability to coordinate outputs from several expertise areas to determine strategyProven track record of effecting substantial changeAbility to make decisionsExpert in integration of preclinical development disciplines and commercial strategy into a full-scale product development activityAbility to influence othersGSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law. #J-18808-Ljbffr