Senior Lead AI Product Manager – Inventory Optimization & ML Allocation

Owns the algorithmic strategy that determines where products go and when, leading a shift from rules-based inventory logic to a predictive, fully machine learning-driven model. It acts as the critical link between data science, logistics, and commercial growth, with a mandate to build intelligent systems that create compounding value for the business. The position sits within the Supply Chain Technology team and works in a cross-functional group of engineers, product managers, and functional consultants who implement features from design to deployment.

• Own the algorithmic strategy that decides where products go and when.
• Lead the rethinking of the inventory approach with data science, building intelligent systems that ensure the right product is in the right place at the right time.
• Take command of the current real-time inventory visibility and inventory allocation system, stabilising its performance while evolving it into a world-class ML platform.
• Partner directly with Supply Chain Operations to build trust in algorithmic decision-making and guide the transition to a fully automated, ML-powered model.
• Partner closely with Data Science & AI teams to architect and guide the development of ML optimisation engines.
• Optimise first allocation (initial launch placement) and balance the cost of over- versus under-allocating across global channels.
• Create and deploy real-time AI agents that scan news, social media, and market signals to automatically rebalance inventory ahead of the curve.
• Drive a clear vision and strategy for the domain, empowering science and engineering teams to solve foundational business problems with cutting-edge technology.
• Act as the critical link between data science, logistics, and commercial growth.
• Build systems that create compounding value for the business.

• 8+ years of experience in Technical Product Management.
• Strong background in both Supply Chain Optimisation and Machine Learning.
• Proven track record of migrating complex legacy or heuristic systems to sophisticated, ML-driven models that listen to and connect with different systems across the technology landscape.
• Experience working closely with Data Science & AI teams, diving deep into data and optimisation models, probabilistic forecasting, and weighing trade-offs such as over- versus under-allocation for first allocation.
• Strong grasp of modern AI capabilities, from NLP and processing unstructured data to building autonomous, decision-making workflows.
• Outcome-obsessed product mindset focused on measurable business outcomes, continuous discovery, and leading with a clear 'why'.

• A passionate team drawn from the global community.
• Encouragement to find new and innovative ways to solve issues through diversity of thought.
• Agile values that are lived, not just talked about.