Responsibilities
:
1. Define and evolve the vision for the data marketplace, ensuring it supports both scientific research and business strategy.
2. Collaborate across departments to implement enterprise-wide data initiatives, applying principles such as data mesh, data as product, and data contracts.
3. Lead the creation and stewardship of high-quality, reusable published information datasets that are easily discoverable and accessible, supporting scientific workflows and compliance.
4. Scout and evaluate emerging technologies to enhance data access, usability, and interoperability.
5. Work closely with business and scientific teams to understand their information workflows and data needs.
6. Ensure seamless, intuitive access to external information from both internal and external sources, reducing friction in scientific data discovery and use.
7. Serve as the primary representative of the data marketplace, delivering presentations, training, gathering feedback, and facilitating co-creation sessions with stakeholders.
8. Champion data quality, interoperability, and contextual enrichment, ensuring external data is ready for advanced analytics and AI applications.
9. Partner with AI and data engineering teams to prepare and optimize data for intelligent systems and scientific platforms.
10. Collaborate with data governance and quality teams to align and develop on enterprise domains, metadata standards, quality indicators, data models, and onboarding materials, all grounded in information science best practices can compliance.
Technical and Professional Competencies:
11. Information Science Expertise
12. Deep understanding of the data lifecycle, metadata, ontologies, and scientific knowledge system.
13. Experience with FAIR data principles (Findable, Accessible, Interoperable, Reusable) and semantic technologies, ensuring data is structured for scientific use.
14. Proven ability to support cross-functional teams through the product lifecycle, from concept to delivery.
15. Familiarity with agile methodologies and product development best practices, especially as they apply to scientific information systems and able to offer guidance on best practice.
16. Awareness of agentic AI, large language models (LLMs), and their implications for scientific data platforms.
17. Ability to assess and integrate innovative tools and technologies into existing scientific data ecosystems.
18. Collaborative leadership style with strong stakeholder engagement skills, fostering collaboration across scientific and business domains.
Disclaimer This vacancy is being advertised by either Advanced Resource Managers Limited, Advanced Resource Managers IT Limited or Advanced Resource Managers Engineering Limited ("ARM"). ARM is a specialist talent acquisition and management consultancy. We provide technical contingency recruitment and a portfolio of more complex resource solutions. Our specialist recruitment divisions cover the entire technical arena, including some of the most economically and strategically important industries in the UK and the world today. We will never send your CV without your permission. Where the role is marked as Outside IR35 in the advertisement this is subject to receipt of a final Status Determination Statement from the end Client and may be subject to change.