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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, AI & Technology Transformation - **Company:** GSK - **Location:** Letchworth Garden City, UK (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Discovery, Data Governance, Data Integration, Data Security, Data Strategy, Data Analytics, Data Management - **Published:** November 7, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/director-ai-technology-transformation/55266738 ## About the Role We are looking for professionals with these required skills to achieve our goals: · Significant experience leading data strategy, data governance, or R&D digital transformation initiatives in a pharmaceutical R&D environment. · Demonstrated experience conducting organizational diagnostics - mapping processes or data journeys, synthesizing pain points, and translating findings into actionable recommendations. · Proven track record of taking a strategy from design through to implementation and delivery. · Experience designing and facilitating workshops or working sessions that build alignment across senior stakeholders and subject matter experts (SMEs). · Experience developing and delivering change plans that include stakeholder engagement, readiness, communications and capability building. · Strong analytical skills, with the ability to assess complex, cross-functional problems and develop a structured, prioritized path forward. · Ability to analyse complex issues, develop practical recommendations and follow through to implementation. · Experience developing business cases, including articulating impact, effort, and feasibility trade-offs. · Working knowledge of data management concepts across data quality, ontology, governance and ownership, data discovery, access and authorization, data integration and platforms, and data products. · Strong communication, facilitation and influencing skills across technical and non-technical stakeholders. · Ability to work independently, manage ambiguity and contribute beyond a narrowly defined change-management remit. · Experience defining measures for adoption, outcomes or value realisation and using data to inform decisions. Preferred Qualifications & Skills: Please note the following skills are not necessary, just preferred, if you do not have them, please still apply: · Experience with R&D data platforms. · Background in management consulting combined with in-house strategy and transformation delivery implementation. · Change-management, project-management or related professional certification. · Experience building and leading cross-functional core teams or workstreams through to delivery. · Familiarity with data governance frameworks, IHD/consent-related data access processes, or regulatory data considerations. · Experience managing delivery-focused teams or programs with direct accountability for outcomes. · Learning, capability-building or workforce upskilling experience., Change Management, Communication, Cross-Departmental Collaboration, Decision Making, Financial Acumen, Innovation, Leadership, Portfolio Management, Project Management, Project Management Governance, Risk Management, Stakeholder Engagement, Stakeholder Management, Strategic Leadership, Visionary Thinking ## Description R&D Tech Transformation & Operations connects strategy, investment and delivery across priority R&D technology programmes. The team works with scientific, technology and business leaders to strengthen decisions, accelerate value and support consistent adoption across R&D. The Director, R&D AI & Technology role leads the diagnosis, design and implementation of R&D's data foundations across its seven core elements - data quality, ontology, governance and ownership, data discovery, access and authorization, data integration and platforms, and data products. You will map end-to-end data journeys, identify systemic pain points, and translate findings into a prioritized set of interventions with clear business cases. You will run sessions with a broad set of R&D leadership, design and run cross-functional workshops to build alignment on the future state, report progress at RDLT level, take direct ownership of implementation and delivery through to measurable outcomes. This is a role for someone who can bring a top-down, strategic picture of R&D's data landscape while staying hands-on through delivery, combining structured diagnostic thinking with strong stakeholder influence and execution rigor. For candidates seeking to be located at our Stevenage site, this role will temporarily be based at Stevenage. However, the Company plans to relocate its offices to Cambridge, UK. The location of this role will therefore subsequently change to Cambridge, UK in accordance with timelines to be set by the Company. The relocation is currently proposed to take effect by early 2029. In this role you will · Lead comprehensive diagnostics of R&D data journeys, reconstructing end-to-end flows from scientific question to data-driven decision across systems, users, and data. · Identify and synthesize pain points across all seven data elements, distinguishing journey-specific issues from systemic, enterprise-wide gaps. · Engage 50+ subject matter experts (SMEs) and core team members across Research, Development, Tech, and AI/ML to ground findings in real user experience. · Define a future-state ambition for priority data-management capabilities. · Run sessions with a broad set of R&D leadership, and design and facilitate cross-functional workshops to align stakeholders on the future state and foundational interventions. · Develop and prioritize interventions based on R&D impact, breadth of reuse, and organizational feasibility, focusing on cross-cutting strategic moves. · Build supporting business cases for priority interventions, including expected impact, effort/cost, and implementation considerations. · Report progress and recommendations at RDLT level, securing leadership endorsement for the roadmap. · Take direct ownership of implementation, leading delivery of prioritized interventions end to end through to measurable outcomes. · Establish workstreams, governance, and ownership structures needed to move interventions. · Identify where existing platforms or initiatives can be leveraged versus where new capabilities are required.