Senior Lead AI Product Manager – Inventory Optimization & ML Allocation

Will build an AI-first intelligence hub from the ground up and own the algorithmic strategy that determines where products go and when within the Supply Chain Technology team. Its purpose is to transition core inventory logic from a rules-based system to a predictive, Machine Learning-driven model that can anticipate and react to market shifts in real time. The role acts as the critical link between data science, logistics, and commercial growth, with a mandate to build systems that create compounding value.

• Own the current real-time inventory visibility and inventory allocation system, stabilising its performance while evolving it into a world-class Machine Learning platform.
• Partner directly with Supply Chain Operations to build trust in algorithmic decision-making and guide the transition to a fully automated, Machine Learning-powered model.
• Partner closely with Data Science and AI teams to architect and guide the development of Machine Learning optimisation engines for first allocation (initial launch placement) and to 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 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.
• Rethink the entire approach to inventory, leading with data science and building intelligent systems that ensure the right product is in the right place at the right time, every time.
• Act as the critical link between data science, logistics, and commercial growth, building systems that create compounding value for the business.
• Own the algorithmic strategy that decides where products go and when.

• 8+ years of experience in Technical Product Management, with a strong background in both Supply Chain Optimisation and Machine Learning.
• Proven track record of migrating complex legacy or heuristic systems to sophisticated, Machine Learning-driven models that listen to and connect with different systems across the technology landscape.
• Experience working closely with Data Science and 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.
• Demonstrated focus on measurable business outcomes, continuous discovery, and leading with a clear 'why' as a product person.