Principal Planning Integration, Fleet Demand, EU Fleet Supply Chain

About the role

Amazon EU Logistics (AMZL) is looking for a Principal Planning Integration professional to lead the re-engineering of its automated Fleet Requirement Planning (FRP) model. The role sits in the EU Fleet Planning & Analytics team, which defines EU fleet requirements to source Armada and rentals, schedule short-term deployments and support business intelligence, with the aim of scaling fleet capacity efficiently.

Key responsibilities

• Re-engineer the FRP model to integrate new van requirements (Ship With Amazon / Delivery Service Partner Lite), move to clustering, probability-based modelling and agentic AI, and scale optimisation models with operational costs as the objective function.
• Evolve the user interface from Excel-based to a dashboard, and integrate new supply channels and netting logics such as van sharing, off-season vans and multi-use vehicles.
• Integrate seamless upstream and downstream approval processes, and scale FRP to middle-mile decisions (CAPEX/OPEX, rental/lease, vehicle mix, asset utilisation).
• Build a digital twin of the FRP models for what-if analysis, scenario planning and investment analysis, in collaboration with Finance and other stakeholders.
• Design scalable fleet demand modelling, forecast accuracy metrics, and ensure plans meet peak demand and are bought in by senior stakeholders.
• Drive the transition to electrification (EV planning) and extend FRP to new business units and countries.

Required profile

• Experience implementing operations solutions such as scheduling, routing, assignment, facility location or lot-sizing.
• Experience with algorithm and model development for large-scale applications, technology transformation and process improvement.
• Strategic planning experience and quantitative problem solving with data-driven recommendations.
• Strong analytical skills, attention to detail and effective communication, including with senior leadership.
• Experience coordinating complex products, working across teams and influencing others.
• Supply chain knowledge (forecasting, planning, sourcing, optimisation, logistics) or equivalent.
• Preferred: Master's degree, or Bachelor's degree with machine learning experience; Lean Six Sigma Green or Black Belt.