AI and Data Strategist
Grade: Senior Manager
Locations: Manchester and London
Position Overview
We are seeking a Senior Manager grade AI and Data Strategist to guide and coordinate AI transformation initiatives for clients across the infrastructure sector. This role demands a strategic business technologist who can translate AI capabilities into tangible business value while designing the organisational frameworks needed to become an AI-first enterprise.
Your client impact
- Lead an engagement workstream consisting of AI consultants and architects to define comprehensive AI and data strategies tailored to client organisations across consumer products, retail, health, energy, and life sciences sectors
- Bring current global thinking and trends in the AI, Automation and Data space including within EY
- Carry out in-depth analysis of infrastructure-specific value chain and identify a portfolio of high impact AI use cases, to drive revenue growth, operational efficiency, and competitive differentiation
- Assess organisational AI and data maturity and create tailored roadmaps for transformation including business cases, operating models, organisational structure and capabilities required to deliver the strategy
- Direct the definition of high-level business and technology architectures and operating models that enable scalable AI deployment (encompassing both data and automation)
- Lead cross-functional workshops and design sessions with senior stakeholders to influence and align diverse stakeholder groups around a unified AI vision
- Present complex AI concepts and recommendations to senior leadership audiences
- Prioritise AI initiatives based on strategic value, feasibility, and organisational readiness
- Contribute to solution development and oversee quality of proposals for AI-led transformation
- Provide mentorship and guidance to team members and develop reusable assets
- Support change management initiatives to embed AI-driven and automation-enabled culture across client organisations, ensuring strategies align with ethical AI principles, regulatory compliance (e.g., GDPR, AI Act), and risk mitigation frameworks
- Support internal processes to approve designs and proposals that have integrity and are commercially sound
Essential Qualifications
- STEM degree or an equivalent certification in Computer Science, Data Science, Engineering, or related field
Essential Criteria
- Strong experience of delivering enterprise-level AI strategies for complex or multinational organisations
- Expertise and interest in the UK Infrastructure sector, including HMG commitments such as National Infrastructure Strategy and the Ten Point Plan for a Green Industrial Revolution
- Experience in designing operating models and organisational structures for data and AI functions
- Experience of working with client organisations to write business or investment cases
- Strong understanding of AI/ML technologies, including generative AI, predictive analytics, NLP, data and Intelligent Automation
- Knowledge of modern data governance frameworks and architectures, cloud platforms, and AI infrastructure including DAMA
- Knowledge of AI governance frameworks, model risk management, and regulatory requirements
- Strategic thinking with demonstrated ability to translate complex technical concepts into business language
Soft Skills
- Team leadership and coaching skills
- Communication and presentation skills
- Stakeholder management skills, including facilitation and workshop design capabilities as well as the ability to influence senior stakeholders
- Demonstrated ability to collaborate in multi-disciplinary teams (data scientists, engineers, business strategists)
- Continuous learning mindset to stay ahead of rapidly evolving AI landscape and strategies for deployment
- Strategic thinking with demonstrated ability to translate complex technical concepts into business language and explain how they drive business value
Preferred Criteria
- Experience with Big 4 consulting methodologies and framework
Preferred Qualification
- Certifications in relevant areas (e.g., cloud platforms, data governance, AI ethics, automation technologies)
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