At a Glance
- Tasks: Lead data strategy and innovation in R&D, shaping the future of healthcare.
- Company: Join GSK, a global biopharma leader committed to improving health worldwide.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Be part of a diverse team driving groundbreaking treatments and innovations.
- Why this job: Make a real impact on global health while working with cutting-edge AI and data science.
- Qualifications: Proven leadership in data science, with hands-on coding and analytical skills.
The predicted salary is between 99000 - 121000 £ per year.
GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centered on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems. Our diverse portfolio consists of vaccines, specialty medicines, and general medicines. Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges.
Are you a seasoned data and data science leader ready to shape how trusted data, advanced analytics, and agentic AI accelerate R&D decisions? Join GSK's Enterprise Data & AI organization as Director of Data & Data Science, Development Data. You will own the strategy, organization, and delivery of data and data science capabilities across R&D, including a portfolio of R&D Data Categories led by Senior Technical Data Product Owners.
In this highly visible leadership role, you will set portfolio strategy, guide people and investment decisions, establish consistent governance and delivery standards, and represent the function with senior R&D and Enterprise Data & AI leaders. You will also remain close to the technology and science: at least 50% of your time will be hands‑on—writing code, building and evaluating models, and developing agentic AI systems that perform trusted data‑science work with appropriate human oversight.
Your responsibilities:
- Shape the R&D data and data science strategy — define an ambitious multi-year vision and translate it into a focused roadmap across all R&D Data Categories.
- Lead the R&D Data Category portfolio — ensure every category has clear ownership, a healthy roadmap, and measurable scientific or business value.
- Direct investment and priorities — balance engineering, data science, platform capacity, technical debt, governance, and innovation across the portfolio.
- Build and develop an outstanding TDPO organization — set clear expectations, resolve cross-category trade‑offs, and lead hiring, organizational design, and career development.
- Champion engineering and data science excellence — embed shared standards, strong review practices, and vibrant communities of practice.
- Safeguard data governance and compliance — drive consistent quality, metadata, access controls, privacy, and audit readiness across R&D data.
- Set the data science and AI agenda — partner with senior scientific leaders to identify, sponsor, and unlock the highest‑value opportunities.
- Create and scale agentic AI data science — personally build systems that explore data, test hypotheses, run analyses, and generate trusted insights with appropriate human oversight.
- Steward technology, funding, and partnerships — shape architecture and tooling, build compelling investment cases, manage budgets, and oversee key supplier relationships.
- Be the voice of the function — influence senior R&D and Enterprise Data & AI leaders and communicate portfolio health, adoption, risk, capacity, and value delivered.
Why You?
Basic Qualification:
- Experience leading a data, analytics, or data science organization in a regulated environment, with accountability for strategy, budget, and multiple direct reports.
- Experience leading leaders, such as product owners, engineering managers, or senior individual contributors who own significant scope.
- Track record of setting and executing a multi-year data and data science strategy that secured senior stakeholder support and funding.
- Technical credibility in data engineering and data science, enabling sound architecture, prioritization, hiring, and escalation decisions.
- Willingness and ability to spend at least 50% of working time hands‑on—writing code, performing analysis, building and evaluating models, and developing agentic AI systems.
- Experience building or deploying agentic AI systems that perform data‑science work, including exploration, hypothesis generation, analysis, and insight generation.
- Working knowledge of R&D data governance, including blinded and unblinded access, GxP considerations, data privacy, and audit readiness.
- Executive communication and stakeholder management skills, with the ability to make portfolio-level trade‑offs across competing priorities.
Preferred Qualification:
- Prior experience as a Technical Data Product Owner, Data Product Owner, or equivalent domain or category‑owning role.
- Familiarity with clinical and life‑sciences data standards, such as CDISC SDTM/ADaM, OMOP CDM, or IDMP.
- Experience operating a formal data‑fabric or data‑mesh model with domain‑oriented ownership and marketplace‑style data product discovery at enterprise scale.
- Experience building or scaling a data science or AI/ML function; an advanced quantitative or life‑sciences degree; or experience with causal machine learning in R&D, clinical, or real‑world data.
Closing Date for Applications: 13th November 2026
Skills: Agentic AI, Artificial Intelligence (AI), Clinical Data, Clinical Development, Database Governance, Data Compliance, Data Science, Data Services, Leadership, Leading by Influence, Machine Learning (ML), OpenAI, People Leadership, Product Strategies, Real World Data, Stakeholder Engagement, Stakeholder Management, Technical Knowledge.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we're committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
GSK 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.
We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.
Head Of Data And Data Science, R&D, Ed&Ai in England employer: GSK
GSK is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Stevenage. With a strong commitment to employee growth, you will have access to extensive development opportunities while working on groundbreaking medicine projects. The hybrid work model and future relocation to Cambridge provide a unique advantage, ensuring a vibrant environment for both personal and professional advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Head Of Data And Data Science, R&D, Ed&Ai in England
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We think you need these skills to ace Head Of Data And Data Science, R&D, Ed&Ai in England
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at GSK, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at GSK. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at GSK
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at GSK!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.