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Are you looking for an opportunity to lead a Translational Data Science team within Oncology Data Science (ODS) in GSK’s Translational Development and Sciences department and aid in the discovery and development of new cancer medicines? If so, this is the job for you. As a Physician Director of the ODS Translational team in the Oncology Data Science you will lead, plan and coordinate applied AI/ML and computational biology projects in partnership with discovery, translational and clinical functions across GSK. You will work in an inter-disciplinary environment, frequently interfacing with wet-lab and translational scientists, clinicians, statisticians, and AI/ML colleagues among others. Your work will have application across Oncology tumor strategy areas and across all stages of drug discovery and clinical development to inform target and biomarker discovery, disease and mechanistic understanding, indication and patient subgroup selection, and treatment response optimization using precision medicine approaches. 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.
Job Responsibility:
Lead and build a growing team of Translational Data Scientists to support and innovate the Oncology portfolio pipeline
Leverage your clinical training and experience to translate complex computational and molecular insights into clinically meaningful hypotheses, study designs, and biomarker strategies that directly inform patient care and oncology clinical development
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. This includes analysis of histopathology imaging data, 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. 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
Requirements:
medical degree
Completion of a clinical residency program leading to board qualification or certification in internal medicine, pathology, pediatrics is required
10 years plus academic or industry experience in Computational Biology, Bioinformatics, or Translational/Clinical AI with focus on Oncology
5 years of leadership or matrix leadership experience in Computational Biology, Applied AI/ML, Cancer Biology or a related field
Nice to have:
A medical degree with PhD is preferred
Leadership with line management experience in Data Science in Oncology Research and Development in Industry, Biotech or Academic settings
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 with multimodal foundation models for preclinical and clinical application in oncology
Experience working with large-scale oncology datasets (e.g., RWE, TCGA, CPTAC and multiomic data integration
Understanding of statistical methods, machine learning and/or AIML algorithms, and survival analysis techniques.
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