Job Description

VP Digital Insights and Artifical Intelligence - UK

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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 company's 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

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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

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Qualifications characteristics

Master's 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.