External Information Solutions Lead

ARM; Slough; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A global biopharmaceutical leader seeks an External Information Solutions Lead in Slough. The role involves defining the data marketplace strategy, implementing data initiatives, and collaborating across departments. The ideal candidate will possess expertise in data lifecycle, FAIR data principles, and demonstrate strong collaborative leadership. This is a full-time position with flexible remote working options.

Qualifications

• Deep understanding of the data lifecycle, metadata, ontologies, and scientific knowledge systems.
• Proven ability to support cross-functional teams through the product lifecycle.
• Collaborative leadership style with strong stakeholder engagement skills.

Responsibilities

• Define and evolve the vision for the data marketplace.
• Collaborate across departments to implement enterprise-wide data initiatives.
• Lead the creation and stewardship of high-quality, reusable published information datasets.

Skills

Information Science Expertise

FAIR data principles

Collaboration

Agile methodologies

Stakeholder engagement

Job description

External Information Solutions Lead

Are you looking for a new role as an External Information Solutions Lead? Do you have a deep understanding of the data lifecycle, metadata, ontologies and scientific knowledge systems? Are you also experienced in FAIR data principles and semantic technologies, ensuring data is structured for scientific use? If so, please click apply today!

We are recruiting for an External Information Solutions Lead on behalf of a global biopharmaceutical leader. This position is offered on a full-time working 37.5 per week on a contract basis initially for 12 months. This position is inside IR35, ideally based in Slough but remote or hybrid applications will be considered.

The successful candidate will report into the Head of Scientific Information and Intelligence and will be responsible for helping to define and execute the team’s data marketplace strategy to enable seamless access to licensed external information assets.

Key Responsibilities

• Define and evolve the vision for the data marketplace, ensuring it supports both scientific research and business strategy.
• Collaborate across departments to implement enterprise-wide data initiatives, applying principles such as data mesh, data as product, and data contracts.
• Lead the creation and stewardship of high-quality, reusable published information datasets that are easily discoverable and accessible, supporting scientific workflows and compliance.
• Scout and evaluate emerging technologies to enhance data access, usability, and interoperability.
• Work closely with business and scientific teams to understand their information workflows and data needs.
• Ensure seamless, intuitive access to external information from both internal and external sources, reducing friction in scientific data discovery and use.
• Serve as the primary representative of the data marketplace, delivering presentations, training, gathering feedback, and facilitating co-creation sessions with stakeholders.
• Champion data quality, interoperability, and contextual enrichment, ensuring external data is ready for advanced analytics and AI applications.
• Partner with AI and data engineering teams to prepare and optimize data for intelligent systems and scientific platforms.
• Collaborate with data governance and quality teams to align and develop enterprise domains, metadata standards, quality indicators, data models and onboarding materials, grounded in information science best practices and compliance.

Technical and Professional Competencies

• Information Science Expertise
• Deep understanding of the data lifecycle, metadata, ontologies, and scientific knowledge system.
• Experience with FAIR data principles (Findable, Accessible, Interoperable, Reusable) and semantic technologies, ensuring data is structured for scientific use.
• Proven ability to support cross-functional teams through the product lifecycle, from concept to delivery.
• Familiarity with agile methodologies and product development best practices, especially as they apply to scientific information systems.
• Awareness of agentic AI, large language models (LLMs), and their implications for scientific data platforms.
• Ability to assess and integrate innovative tools and technologies into existing scientific data ecosystems.
• Collaborative leadership style with strong stakeholder engagement skills, fostering collaboration across scientific and business domains.