Product Owner

The Opportunity: 

We are looking for an experienced IT Product Owner to lead the Finance Forecasting Hub.

The role sits at the intersection of Finance, advanced analytics, machine learning, GenAI and agentic AI. You will act as a thought partner to Finance leaders, turning ambiguous business problems into clear product outcomes and shaping effective technical solutions. 

You will own the path from problem framing and discovery through prioritisation, MVP, production and scaling. Success means delivering useful capabilities quickly, simplifying complexity and dependencies, and building trust across a demanding global stakeholder landscape. 

Key Responsibilities:

Product Strategy & End-to-End Ownership 

• Co-create product outcomes, success measures and epics with Finance customers; challenge assumptions and clarify the problem before defining the solution. 

• Translate strategy into a focused roadmap and the smallest valuable increments, features and user stories. 

• Own and prioritise the product backlog based on business value, learning, risk, dependencies and capacity. 

• Maintain a clear medium- and long-term roadmap while adapting quickly as evidence and priorities change. 

AI Product Leadership 

• Identify and shape technical solutions for the business problems. 

• Partner with Applied AI, data and engineering experts to select fit-for-purpose approaches and define data, model, evaluation and integration needs. 

• Drive AI-enabled capabilities from discovery and experimentation into production, adoption and measurable business outcomes. 

• Make informed product decisions on AI quality, limitations, human-in-the-loop design, risk, privacy, governance and operational sustainability. 

Delivery & Value at Speed 

• Lead delivery with the Scrum Master and squad, maintaining clear ownership of product decisions and outcomes. 

• Use prototypes, experiments and MVPs to shorten learning cycles and deliver value early. 

• Remove blockers, reduce dependencies and simplify scope before adding process or coordination. 

• Make pragmatic trade-offs between value, speed, quality, risk and complexity. 

• Continuously improve time to value using outcome and delivery metrics. 

Squad & Ecosystem Leadership 

• Shape squad capabilities to match planned increments, bringing in the right product, engineering, data, analytics, ML, AI and Finance expertise. 

• Create clarity for the squad on the problem, priorities, acceptance criteria and definition of success. 

• Partner effectively with the Applied AI organisation to align on architecture and technology. 

Stakeholder Thought Partnership & Leadership 

• Act as a trusted thought partner to Finance customers, combining curiosity, constructive challenge and product judgment. 

• Navigate competing priorities, ambiguous ownership and conflicting stakeholder needs; create alignment without waiting for perfect consensus. 

• Facilitate difficult scope and prioritisation decisions using evidence, business value and transparent trade-offs. 

• Balance global reusable capabilities with legitimate local needs. 

• Communicate credibly with senior business leaders and technical teams, especially when decisions are difficult or uncertain. 

Experience & Capabilities:

Must-have: 

• Strong end-to-end product ownership experience for complex digital products, with clear accountability for outcomes rather than only project delivery or backlog administration. 

• Demonstrated record of delivering measurable value at speed through prioritisation, MVP thinking, fast learning cycles and dependency reduction. 

• Deep practical knowledge of applying advanced analytics, machine learning, GenAI and/or agentic AI to business problems, including shaping technical solutions and understanding the trade-offs and limitations of these approaches. 

• Practical experience shaping and delivering AI-enabled products or capabilities, with a clear understanding of production, adoption and evaluation considerations. 

• Proven ability to act as a thought partner to internal customers: frame problems, challenge assumptions, shape options and influence decisions. 

• Proven ability to navigate complex global stakeholder situations, competing priorities and cross-product dependencies. 

• Strong Agile product delivery, roadmap and backlog-prioritisation skills. 

• Experience shaping multidisciplinary teams and working across product, engineering, data and business functions. 

Strong advantage: 

• Understanding of Finance processes, especially planning, forecasting or FP&A. 

• Previous pharmaceutical experience or experience in a comparable large, regulated enterprise. 

Critical Screening Criteria: 

• End-to-end product ownership with clear evidence of outcome accountability. 

• Deep practical AI product knowledge and evidence of applying AI to real business problems. 

• Demonstrated ability to deliver value at speed and simplify scope, dependencies and decision-making. 

• Strong thought-partnership skills with internal customers. 

• Proven ability to navigate complex, senior and global stakeholder situations. 

Finance process knowledge is an advantage and should strengthen a candidate's score, but it is not a screening requirement. The strongest candidates will combine product judgment, practical AI depth, fast execution and stakeholder thought partnership.

Tech stack

• Product Ownership
• Advanced Analytics
• Machine Learning
• GenAI
• AI product leadership
• agile delivery
• Backlog prioritisation
• Stakeholder Management