AI-Ready Data Foundations Lead in Slough

AI-Ready Data Foundations Lead in Slough

Slough Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead the creation of AI-ready data foundations and govern data standards.
  • Company: Join UCB, a leader in patient solutions and innovation.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on innovation and career advancement.
  • Why this job: Make a real impact by enabling scalable data for research and operations.
  • Qualifications: Experience in data governance and strong collaboration skills required.

The predicted salary is between 60000 - 80000 Β£ per year.

UCB is seeking a Data Foundations Lead to join the Patient Solutions Digital Strategy & Innovation team in Slough, UK (Windlesham from 2027). You will establish enterprise data foundations, govern metadata, ontologies and data standards to enable scalable, AI-ready data across R&D and operations.

You will collaborate with scientific, digital and enterprise teams, design conceptual and logical data models, promote FAIR data practices, and deliver reusable data products to accelerate research.

AI-Ready Data Foundations Lead in Slough employer: UCB S.A.

UCB S.A. is an exceptional employer that fosters a collaborative and innovative work culture, particularly in the field of immunology. With a strong commitment to employee growth and development, you will have access to unique opportunities for professional advancement while working in a hybrid environment that promotes work-life balance. Join us in making a meaningful impact on patient outcomes across the UK and Ireland, where your contributions will be valued and recognised.

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Contact Details:

UCB S.A. Recruitment Team

We think you need these skills to ace AI-Ready Data Foundations Lead in Slough

Data Governance
Metadata Management
Ontology Development
Data Standards Implementation
AI Readiness
Collaboration Skills
Conceptual Data Modelling