Principal Data Advisor - Life Sciences

Who You'll Be Working With

The Data Powered Industries and Domains (DPID) team, part of Capgemini’s Insights and Data practice in the UK, is growing its Domain Aligned capability. Join a team that sits at the heart of our most important client relationships, advising on complex data, AI and analytics challenges with deep expertise across the entire delivery lifecycle.

We build trusted partnerships with senior stakeholders by translating business needs into technology solutions and measurable outcomes. As a key driver of growth, we help shape and advance our clients’ data and AI vision and capabilities.

The Focus Of Your Role

As a Pharma R&D Data Advisory Lead, you will serve as a trusted advisor to Life Sciences clients, helping them define and execute strategies that transform pharmaceutical Research & Development through data, AI, semantic technologies, and intelligent automation. Working with senior business and technology stakeholders, you will translate complex scientific, research, clinical, and data challenges into practical transformation roadmaps, operating models, and technology strategies that deliver measurable business outcomes.

You will help clients establish the foundations for intelligent R&D by combining trusted data, governance, semantic models, interoperability, advanced analytics, and AI-enabled decision support. Your focus will be on enabling connected, governed, and context-rich R&D data ecosystems spanning Discovery Research, Translational Sciences, Preclinical Development, Clinical Development, Regulatory, and Safety functions. These capabilities support scientific innovation, better decision-making, operational efficiency, regulatory compliance, and the responsible adoption of AI across the pharmaceutical R&D lifecycle.

Key Responsibilities

Key responsibilities include:

Advise Life Sciences clients on transforming pharmaceutical R&D through the effective use of data, analytics, AI, and automation. Assess current capabilities, identify opportunities for improvement, and develop business-focused strategies and roadmaps that accelerate scientific innovation, improve development productivity, enhance data quality, and enable better decision-making across Discovery, Research, Preclinical, Translational, and Clinical functions.

Partner with Discovery Sciences, Research Informatics, Translational Medicine, Clinical Development, Clinical Operations, and R&D Technology leaders to align technology investments with business objectives and measurable outcomes.

Data Strategy, Governance & Semantic Technologies

• Help clients establish trusted and connected R&D data foundations through governance, master data management, interoperability, metadata management, and modern data architectures. 
• Lead the application of semantic technologies, ontologies, RDF-based knowledge graphs, and common data models to create a shared understanding of scientific, research, preclinical, and clinical information across systems.
• Enable advanced analytics, scientific knowledge management, intelligent automation, and AI-powered decision support while ensuring compliance, data integrity, traceability, and governance across the R&D landscape.

AI & Intelligent R&D

• Identify and shape high-value opportunities for AI, advanced analytics, GenAI, and intelligent automation across the pharmaceutical R&D lifecycle.
• Provide guidance on AI readiness, use case prioritisation, governance, and responsible adoption, helping clients realise business value from emerging technologies while ensuring solutions are built on trusted, compliant, and well-governed data.

Architecture & Technology Leadership

• Provide strategic direction on R&D data, AI, analytics, and enterprise architecture, helping clients design scalable and future-ready solutions.
• Work with business and technology teams to define architectures, operating models, and implementation approaches that improve interoperability, reduce complexity, and enable intelligence to operate effectively across the pharmaceutical R&D technology landscape.

Client Relationship Management & Business Development

• Build trusted relationships with senior client stakeholders and act as a strategic advisor on R&D data, AI, scientific informatics, and digital transformation initiatives.
• Support business development activities through opportunity identification, proposition development, solution shaping, thought leadership, proposal development, and client presentations.
• Collaborate with account and delivery teams to grow strategic client relationships, expand engagements, and help clients realise measurable value from their data and AI investments.
•  Contribute to the growth of Capgemini's Life Sciences and Insights & Data practice through knowledge sharing, mentoring, and the development of reusable assets and industry-leading propositions.

What You'll Bring

You'll bring a blend of pharmaceutical R&D domain expertise, consulting and advisory experience, architecture knowledge, and strong data and AI capabilities. You'll be comfortable engaging senior stakeholders, communicating complex ideas clearly, navigating ambiguity, building trusted relationships, and collaborating across business and technology teams to deliver meaningful outcomes.

Anyone from Discovery Informatics, Research Informatics, Translational Sciences, Preclinical Development, Clinical Development, R&D Technology, Scientific Data Management, Data & AI, or broader pharmaceutical R&D backgrounds would be welcome to apply.

Experience:

We know that great candidates don't always meet every requirement. If you're excited about this role and feel you bring many of these qualities, we'd love to hear from you.

• Experience within pharmaceutical R&D, spanning Discovery, Research, Translational, Preclinical, Clinical Development, Regulatory, Safety, or associated business and technology functions. 
• Experience leading advisory, consulting, data, digital, AI, or business transformation initiatives within the Life Sciences sector. 
• Strong understanding of pharmaceutical R&D data, governance, regulatory requirements, and industry standards, with experience establishing trusted, interoperable, and scalable data foundations. 
• Experience applying data, analytics, AI, GenAI, automation, semantic technologies, knowledge graphs, and modern information architectures to solve scientific, research, and clinical business challenges. 
• Experience working with Life Sciences technology ecosystems, including scientific informatics, laboratory, clinical, regulatory, and safety platforms. 
• Familiarity with modern cloud, data, and AI platforms, alongside contemporary data architectures, operating models, master data management, and data product approaches. 
• Demonstrated experience advising senior stakeholders, building trusted client relationships, and translating business challenges into data, technology, and transformation strategies. 
• Experience developing business cases, target operating models, strategic roadmaps, and transformation programmes that deliver measurable business value. 
• Experience supporting business development activities, including opportunity identification, solution shaping, proposal development, bids, and client presentations. 
• Experience leading or contributing to complex, multidisciplinary programmes while balancing strategic thinking with pragmatic delivery.

Must Have Skills

• Deep understanding of pharmaceutical R&D processes, including Discovery Research, Translational Sciences, Preclinical Development, Clinical Development, and associated data ecosystems.
• Strong understanding of modern data and AI architectures and how they deliver business value.
• Ability to translate complex technical concepts into clear, actionable insights for both technical and non-technical audiences.
• Strong communication, facilitation, consulting, and storytelling skills, with the ability to influence senior stakeholders.
• Collaborative mindset with excellent interpersonal and relationship-building skills.
• Comfortable working in ambiguity and helping define both problems and solutions.
• Commercial awareness and the ability to identify opportunities to create value for clients.
• Passion for continuous learning and curiosity about emerging technologies, industry trends, and best practices in data, AI, and Life Sciences.
• Commitment to knowledge sharing, mentoring, and fostering a learning culture.

Additional Info