VP Digital Insights and Artifical Intelligence UK

We are seeking a highly capable and strategic VP Digital Insights and Artificial Intelligence to lead on own the strategy implementation and governance of data analytics and AI platform architecture across the organization. This newly created role is responsible for shaping the companys approach to information management enterprise data management which includes data governance data quality and data management; analytics predictive analytics and AI while also ensuring the design delivery and continuous improvement of the underlying technology platforms that enable these capabilities.

This leader will partner with business stakeholders IT and data science teams to identify high-value opportunities deliver innovative and responsible AI solutions and build a robust scalable architecture that supports insight generation process optimization and automation.

Location: UK

Reports to: Directly reporting to the CIO

Your Role in our Future

The VP of Digital Insights and AI is entrusted with the following tasks:

Leadership

• Define and lead the enterprise-wide Digital Insights & AI Platform Strategy ensuring alignment with business priorities and long-term technology roadmaps
• Establish governance frameworks for data analytics and AI to ensure quality security and ethical use
• Drive adoption of AI automation and analytics solutions across business functions to maximize ROI and efficiency

Information and Data Management

• Lead the development and maintenance of information management and enterprise data management frameworks to ensure data quality consistency and availability
• Oversee data integration taxonomy metadata management and data stewardship initiatives
• Ensure proper architecture and tooling for data pipelines data lakes and enterprise reporting platforms
• IT Platform Architecture & Delivery

Platform Architecture and Delivery

• Own the design delivery and evolution of enterprise technology platforms that enable data analytics and AI

• Define the technical architecture (data application integration and cloud architecture) to support business needs scalability and resilience
• Partner with IT delivery teams to ensure timely implementation of platform enhancements and upgrades
• Evaluate and select technology solutions (BI tools ML platforms automation frameworks) that align with the enterprise architecture and future-proof the business.

Analytics & Insights

• Build and partner on advanced analytics and business intelligence capabilities to deliver actionable insights

• Develop predictive and prescriptive analytics use cases that inform strategic decisions and improve operational outcomes
• Champion self-service analytics and empower business teams to access and use data confidently

Responsible Artificial Intelligence & Automation

• Identify evaluate and deliver AI initiatives including:
• Conversational AI (e.g. chatbots virtual assistants)
• Intelligent Automation (RPA AI-driven decisioning)
• Machine Learning and Predictive Models for forecasting and optimization
• Collaborate with product operations and technology teams to embed AI into products services and workflows
• Drive process optimization initiatives using AI insights to reduce friction and improve efficiency

Collaboration & Stakeholder Engagement

• Act as a trusted advisor to business and IT stakeholders identifying opportunities where AI and analytics can create business value
• Build strong relationships with internal and external partners (vendors technology providers consultants) to accelerate capability building
• Lead change management efforts to drive adoption of digital intelligence solutions and foster a data-driven culture

Team Leadership & Capability Building

• Support the building of high-performing team of data analysts data scientists solution architects and AI/automation specialists
• Develop and deliver education and training programs on data literacy analytics and AI best practices
• Stay abreast of emerging trends and technologies in AI machine learning cloud platforms and analytics to inform strategic decisions

Your Profile

Qualifications characteristics

• Masters degree or PhD in Computer Science Data Science Artificial Intelligence Machine Learning Engineering or a related field
• Executive education or certifications in AI strategy digital transformation or innovation (e.g. MIT Stanford INSEAD programs)
• Certifications in cloud platforms (AWS Azure GCP) and data governance frameworks are a plus

Essential Experience

• 8 years of experience in data analytics AI or IT platform leadership roles
• Proven track record of designing and delivering enterprise platforms for data and analytics
• Demonstrated success in deploying AI automation and predictive analytics initiatives that drove measurable business outcomes
• Strong knowledge of enterprise architecture data governance and platform delivery methodologies (Agile/DevOps)

Technical Competencies

• Deep expertise in:
  • Machine learning deep learning NLP computer vision
  • Data engineering big data platforms and analytics
  • AI/ML model lifecycle management (MLOps)
  • Cloud-native architectures and scalable AI infrastructure
• Strong understanding of emerging technologies (e.g. generative AI edge AI synthetic data)

Strategic & Business Acumen

• Ability to translate complex AI capabilities into business value
• Experience developing and executing digital intelligence strategies aligned with corporate goals
• Strong financial acumen and experience managing large budgets and vendor ecosystems
• Familiarity with industry-specific use cases (e.g. predictive analytics automation personalization)

Leadership & Communication Skills

• Visionary leadership with the ability to inspire and mobilize cross-functional teams
• Excellent stakeholder engagement skills including C-suite and board-level communication
• Experience in change management and fostering a data-driven culture
• Strong presentation and storytelling skills to communicate AI impact

Soft Skills

• High emotional intelligence and adaptability
• Ethical mindset and commitment to responsible AI
• Collaborative and inclusive leadership style
• Resilience and ability to navigate ambiguity and complexity

Desirable

• Experience with international operations and multicultural teams
• Thought leadership in AI (e.g. publications speaking engagements)
• Active involvement in AI communities consortiums or advisory boards

Success Metrics

• Delivery of scalable secure and high-performing technology platforms supporting analytics and AI
• Increased data quality and availability across business functions
• Successful deployment and adoption of AI and automation initiatives
• Demonstrated business value from predictive and prescriptive analytics use cases
• Improved collaboration between business and IT teams on data-driven projects.
• Enhanced organizational data literacy and digital intelligence maturity.