- Own and drive the AI strategy from opportunity identification through deployment, adoption and value realisation.
- Redesign business workflows around AI, focusing on practical outcomes.
- Build AI capability through training, prompt libraries, templates and a network of AI champions.
- Measure and report AI adoption, success metrics and lessons learned.
- Own the business-facing gold layer of the data warehouse, including metrics, definitions and quality standards.
- Develop and extend the semantic data model for consistent access to business data.
- Champion data self-service across teams.
- Establish analytics engineering best practices for testing, version control, documentation and code reviews.
- Simplify and improve the quality of the data estate.
- Deliver proactive insights and recommendations to senior leadership.
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