Product Owner - AI Fraud Operations

NatWest is a major UK retail bank, providing every day banking services to over 19 million customers. The banks expertise and services span retail, commercial and private banking.

AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces. We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent strategies.

We partner with NatWest to deliver their contingent recruitment processes. Acting as an extension of their recruitment teams, we connect them with skilled interim and temporary professionals, fostering workplaces where everyone can contribute and succeed.

On behalf of NatWest, we are looking for a Product Owner - AI Fraud Operations for a 6 Month Day Rate Contract based in London. Please note this is a hybrid working model.

Job Description - The Role

As a Product Owner, you will join the AI capability programme designed to support Fraud Operations with clearer, faster and more consistent investigations. Its multi-agent framework can summarise cases, explain risk signals and generate tailored investigative questions. The product is moving from controlled experimentation towards production and broader use, with success dependent on safe AI, high-quality data, operational adoption, measurable outcomes and effective integration with colleague tooling.

What you'll do:

• Work as the delivery team-facing Product Owner, providing clear day-to-day product direction and maintaining close alignment with the Lead Product Owner.
• Own and communicate the product vision, outcomes and roadmap, extending the capability beyond its initial payments and scams use cases where evidence supports expansion.
• Turn Fraud Operations needs into a prioritised product backlog covering investigator journeys, summaries, explanations, investigative questions, data sources and future specialist agents.
• Lead discovery, experiments and evaluation with investigators, using qualitative feedback and measurable evidence to decide whether to stop, pivot, improve or scale capabilities.
• Define success measures for decision quality, investigator productivity, customer protection, operational efficiency, adoption and responsible AI performance.
• Partner with data science, machine learning engineering, data engineering, architecture, operations, risk and technology teams to shape safe, usable and scalable solutions.
• Prioritise the data roadmap, ensuring each source has a clear risk-profiling purpose, appropriate ownership, quality expectations, latency needs and a strategic or proportionate tactical route.
• Own product requirements and acceptance criteria for model and agent behaviour, explanations, user experience, controls, monitoring, guardrails and production readiness.
• Navigate AI, model, data, privacy, security, accessibility and design governance, maintaining momentum while ensuring risks and decisions are transparent.
• Coordinate integration with colleague tooling and future channels, while preserving a modular design that supports new use cases and specialist agents.
• Build senior stakeholder confidence through a clear product story, roadmap, evidence base, benefits case and honest view of dependencies and trade-offs.

The skills you'll need:

You’ll be a confident, outcome-focused product professional who is comfortable working through ambiguity and bringing together business, operational and technical perspectives.

• Product ownership experience delivering AI, data, analytics or colleague-facing digital products from discovery and experimentation through production adoption.
• Ability to frame ambiguous operational problems, form testable hypotheses and turn learning into product decisions and prioritised delivery.
• Understanding of generative or agentic AI product considerations, including evaluation, explainability, guardrails, human oversight, data quality, monitoring and responsible use.
• Strong user-centred product skills, with experience working directly with operational users and translating feedback into valuable, usable capabilities.
• Confidence working across data science, engineering, architecture and risk teams, translating technical complexity into clear decisions and stakeholder narratives.
• Strong senior stakeholder management, with the ability to align competing priorities across operations, product, technology, data and governance.
• Commercial and outcome focus, including business cases, measurable benefits, adoption metrics and value realisation.
• Strong Agile product practices across roadmap management, backlog prioritisation, user stories, acceptance criteria and iterative delivery.

Next Steps

There are plenty of reasons why NatWest is a great place to work in a temporary job; they are becoming a simpler Bank, which is more integrated and technology driven. You'll be helping to build a sustainable bank, committed to helping customers to succeed.

We will only accept workers operating via an Umbrella or PAYE engagement model.

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