Director, Data Policy & Standard Procedures Lead

GSK

About The Position

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. GSK has kicked off 2026 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. Design policy that moves at the speed of science: Director – Data Policy & Standard Procedures Lead If you believe data policy should enable confident decisions, not create friction, this role is for you. We’re looking for a strategic builder who can modernise how data policies and standards are designed, delivered, and experienced across R&D. This is not a document‑driven role. Think policy‑as‑product, policy‑as‑code, and standards that are embedded directly into platforms and workflows. Your mission is to ensure our data policies are clear, actionable, interoperable, and adopted by default, so teams can move faster while staying compliant and ethical by design.

Requirements

Bachelor’s degree in computer science, Data Management, Mathematics, Statistics, Biostatistics, or a related field.
Excellent communication and stakeholder engagement abilities.
Strong leadership, team management, and stakeholder engagement skills.
Demonstrated ability to drive continuous improvement, innovation and manage complex data projects.
Broad experience in clinical development processes and R&D data lifecycle.
Proven experience of policy lifecycle management and governance operating models
Demonstrated experience operating in matrix (hub and spoke) organizational structures, working with policy development, quality systems or standards frameworks within regulated environments
Proven capability to translate complex technical or regulatory requirements into clear and actionable policies or procedures
Proven experience of GxP, data privacy, and regulatory compliance requirements (e.g., GDPR, HIPAA).

Nice To Haves

Master’s degree in computer science, Data Management, Mathematics, Statistics, Biostatistics, or a related field.
Certification in data governance or data management frameworks (e.g., DAMA/DMBOK, DCAM, EDM Council) strongly preferred.
Experience in AI governance, responsible AI, and machine learning operations (e.g., AI ethics programs, LLMOps/MLOps certificates) strongly preferred.

Responsibilities

Set the vision for data policy and standards as a core governance product that underpins R&D digital transformation, grounded in regulatory rigor (GxP, GDPR, HIPAA) and designed for usability and scale.
Own the end‑to‑end policy lifecycle, from user research and design through codification, automation, rollout, and continuous improvement.
Modernise policy delivery by operationalising policy‑as‑code and embedding standards directly into platforms, workflows, and decision points across R&D.
Act as the central policy hub within a federated (hub‑and‑spoke) governance model—setting guardrails, patterns, and assurance while enabling domains to move fast locally.
Champion user‑centric policy design, partnering with data owners, stewards, engineers, and scientists to reduce ambiguity and friction in real‑world usage.
Prioritise and manage a transparent policy backlog, applying product management techniques (value vs effort, MVPs, user stories) to deliver the highest impact first.
Ensure compliance, ethics, and risk management by proactively identifying gaps, addressing inconsistencies, and escalating issues where needed.
Measure and communicate impact, defining KPIs for adoption, effectiveness, and risk reduction, and translating governance outcomes into business value.
Continuously scan for innovation, bringing emerging best practices in governance, knowledge management, and automation into the policy ecosystem.