Manager, Translational Biomarker Data Pathways & Re-use

Benefits

Additional Information

The R&D Translational Sciences (TS) team at GSK is a world-class centre of excellence in genetics, genomics and translational science focused on generating genetic and genomic insights into Research Unit-directed disease and product strategies. Our operating principles include end-to-end translation, strong integration between translational leads and core functional teams, and excellence in foundational capabilities while increasing earlier translational impact. Reporting to the Senior Director, Translational Samples & Informatics, this role provides operational leadership to set up, stabilise and scale end-to-end (E2E) translational data pathways, including enabling re-use of clinical datasets at scale to support translational research and decision-making. A key objective of this role is to help evolve translational biomarker datasets from one-off outputs into reusable, accessible data assets; available, interpretable and usable across multiple translational use cases. The role operates across a spectrum of technology and system maturity: providing hands-on leadership where processes are new or fragmented, and building repeatable, scalable ways of working as systems mature, transitioning into business as usual with matrix partners. This role delivers Translational Sciences and GSK pipeline objectives by connecting and aligning delivery across internal and external partners (including R&D Digital & Tech (RDDT), Platform Sciences, Research & Development Technologies (R&D Tech), Biostatistics & Programming, and AIML), to support impactful use and re-use of human data for translational activities. We create a place where people can grow, be their best, be safe, and feel welcome, valued and included. We offer a competitive salary, an annual bonus based on company performance, healthcare and wellbeing programmes, pension plan membership, and shares and savings programme. We embrace modern work practises; our Performance with Choice programme offers a hybrid working model, empowering you to find the optimal balance between remote and in-office work. Discover more about our company wide benefits and life at GSK on our webpage Life at GSK | GSK In this role you will Translational dataset use & re-use at scale (core accountability): Lead the end-to-end enablement of biomarker dataset re-use (clinical & non-clinical)by helping ensure data is findable, accessible, interpretable and aligned to translational decision-making timelines. Identify and drive resolutiion of systemic barriers (for example: unclear ownership, access constraints, metadata gaps and platform fragmentation). Establish repeatable, scalable end-to-end (E2E) pathways. E2E data pathway delivery: When needed, lead the set-up and delivery of complex end-to-end biomarker data pathways across multiple functions, defining data flows, roles, responsibilities and dependencies. Stabilisation & pattern development: Support the transition of pathways into stable, repeatable models, and codify ways of working into standard processes, templates and reusable patterns. Alignment to decision timelines: Align data delivery or access with analysis readiness and translational decision milestones to maximise impact for GSK's portfolio. Operational data ownership: Act as an operational focal point for Translational Sciences data flows, helping ensure delivery aligns with enterprise governance frameworks and working in partnership with Data Automation and Predictive Sciences, Platform Sciences Data Operations and the Development Data Value Office. Reducing reliance on senior intervention to align teams and resolve data pathway challenges. Portfolio visibility: Develop and maintain visibility of active Translational Sciences data assets, pathways and re-use opportunities to proactively identify risks, opportunities and priorities. Continuous improvement: Monitor data-related performance and drive improvements to increase reliability, accelerate progress and reduce manual intervention. Why you? Basic Qualifications & Skills: We are looking for professionals with these required skills to achieve our goals: MSc (or equivalent) in relevant discipline. Significant experience working with human biomarker or high-dimensional data types in Pharma/Biotech, academia, healthcare, or a similar complex R&D environment. Ability to solve complex, cross-functional data and/or technology challenges, using a structured and collaborative approach Strong stakeholder management skills in matrix organisations Working knowledge of data governance and operational data flows (for example FAIR and data integrity principles) Strong organisational and prioritisation skills Ability to lead in areas of ambiguity, bringing clarity and direction while partnering effectively with others Preferred Qualifications & Skills: Please note the following skills are not necessary, just preferred, if you do not have them, please still apply: Experience working in multi-cloud and/or multi-platform environme