Have you ever wondered how Amazon delivers so quickly, or if delivery speeds could improve even further? In the Amazon EU Placement & Inbound Supply Chain team, we drive innovation for our customers to enhance product availability and speed while reducing costs and carbon emissions on the end-to-end supply chain from Selling Partners. This role will give an unique view into Amazon Inbound and Inventory Placement systems, processes, and operations, enabling collaboration with planning, operations, and technical teams. Among others, you will have the opportunity to simplify our supply chain network to deliver faster and cheaper. If you excel at understanding complex systems and have a proven track record of analyzing data to generate insights and business recommendations at scale, we'd like to talk to you.

This position is based out of our UK Headquarters in London.

Key job responsibilities
• Build and maintain metrics to evaluate and enhance Inbound performance of Selling Partners and Amazon network.
• Create analytical tools and processes to accelerate insights and automation.
• Drive inbound and placement strategy improvements using data modeling and analysis to optimize product spread across Amazon facilities, enhancing selection and reducing distance.
• Collaborate with technology teams to define key priorities to accommodate growing business needs and implement recommendations through new features and/or configurations.
• Research, develop, document and present new opportunities to all levels of Supply Chain, Finance and Retail leadership.

A day in the life
• Collaborate with a diverse team of Business Intelligence Engineers, Data Scientists, Program or Product Managers and Finance Analysts to develop effective metrics and analytical tools that address business goals.
• Partner with Business and Tech teams to prioritize impactful insights.
• Explore systems while performing anecdotes to understand concrete root causes.
• Scale findings from anecdotes to understand its impact and respective prioritization.
• Conduct data driven experiments to accelerate innovation.
• Perform analysis at scale with new metric cuts and/or statistical models.