Product Owner

AI Product Owner – Banking

The opportunity

We’re working with a leading financial services organisation that is scaling its AI and data capabilities across the bank. They’re looking for an experienced AI Product Owner to take ownership of high‑impact AI initiatives, helping turn complex business problems into trusted, compliant, production‑ready AI products . This would be a contract role, outside IR35.

This role sits at the heart of business, technology, data science, and risk, and is ideal for someone who is comfortable delivering in a regulated, high‑scrutiny environment.

What you’ll be doing

• Own the product vision, roadmap, and backlog for one or more AI‑driven products or platforms
• Translate business goals into AI use cases, hypotheses, and measurable outcomes
• Work hands‑on with data scientists, ML engineers, and data engineers to shape data and model requirements
• Prioritise delivery across data readiness, model development, experimentation, and release
• Act as the bridge between business stakeholders, technology, risk, legal, and compliance
• Ensure AI solutions are explainable, usable, and appropriate for customers and colleagues
• Embed Responsible AI principles, including fairness, transparency, and accountability
• Define and track success metrics across business value, user adoption, and model performance
• Support AI products through deployment, monitoring, and continuous improvement

What we’re looking for

• Proven experience as a Product Owner / Product Manager delivering AI‑ or data‑driven products
• Experience working in banking or financial services (or other heavily regulated environments)
• Strong understanding of:
• Machine learning concepts and limitations (no coding required)
• Data quality, model evaluation, and performance trade‑offs
• Comfortable operating in Agile / Scrum environments
• Ability to explain complex AI topics clearly to non‑technical stakeholders
• Strong judgement around risk, ethics, and governance

Nice to have

• Experience in areas such as fraud, credit risk, financial crime, customer operations, or GenAI
• Exposure to model risk management or regulatory engagement
• Experience working with AI platforms, MLOps, or enterprise data ecosystems