AI & Data Analytics Manager

AI will only create value when it is trusted, explainable, usable and connected to real operating priorities. Your challenge will be to establish the conditions for responsible AI adoption while also proving the value of delivery.

You will assess the current environment, define a pragmatic AI strategy, create an ethical and auditable governance model, identify the first high-value opportunity, and help deliver a practical capability. You will work across technology, data, legal/regulatory, commercial and operational stakeholders, translating complexity into decisions and a roadmap that the organisation can maintain.

This role will suit someone who enjoys ambiguity, ownership and building from zero. It will not suit someone looking only for a strategy, policy, presentation or vendor-management mandate.

The role is expected to succeed within a Microsoft-driven AI, data and application ecosystem. Relevant experience includes:

• Azure AI and machine learning: Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Azure AI Search, model registries, managed endpoints, evaluation, monitoring and responsible-AI controls.
• Data engineering and analytics: Microsoft Fabric, OneLake, Fabric Data Factory, Azure Data Factory, Azure Data Lake Storage Gen2, Azure SQL and Azure Synapse Analytics.
• Data governance and insight: Microsoft Purview, data cataloguing, lineage, classification, quality controls, semantic models and Power BI reporting.
• Application and integration: C#, .NET / ASP.NET Core, REST APIs, Azure Functions, API Management, Logic Apps, Service Bus and event-driven integration patterns.
• Security and platform foundations: Microsoft Entra ID, role-based access control, managed identities, Azure Key Vault, private endpoints, Azure Policy, Microsoft Defender for Cloud, Azure Monitor and Application Insights.
• DevOps and MLOps: GitHub or Azure DevOps, Git, CI/CD, infrastructure as code using Bicep, ARM or Terraform, containerised deployment, model/version management, automated testing, release controls and production monitoring.

You will bring evidence of the following:

• A minimum of five years’ experience in technology and a minimum of five years leading AI initiatives at scale, as required by the vacancy record.
• Demonstrated experience taking AI or advanced-analytics work end-to-end: problem definition, data, model/solution selection, architecture, development, deployment, monitoring and improvement.
• Hands-on experience in a Microsoft-driven environment, ideally across a meaningful combination of Azure AI/ML, Microsoft Fabric or Azure data services, Power BI, C#/.NET integration, Microsoft security/governance and Azure DevOps or GitHub-based delivery.
• Proven experience establishing or operating AI governance, ethical oversight, risk controls, explainability or auditability in a real organisation.
• Evidence of building a new capability, function, operating model or roadmap where the path and resources were not already defined.
• Strong stakeholder leadership across technology, data, legal/regulatory, commercial and operational audiences.
• The judgement to balance hands-on delivery with strategy, governance, adoption and commercial realities.
• Financial-services, fintech, telco or another regulated-environment background is advantageous, but transferable evidence from a complex, highly governed environment should be considered.
• A Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics or a related field. A Master’s/PhD and relevant AI/ML, cloud or data-science certifications are advantageous.
• Registration with a relevant professional body, subject to final confirmation of the accepted requirement.
• Comfort working independently at the start of a mandate, without an established AI team or mature playbook.