Economic Decision Science is a central science team working across a variety of topics in the EU Stores business and beyond. We work closely EU business leaders to drive change at Amazon. We focus on solving long-term, ambiguous and challenging problems, while providing advisory support to help solve short-term business pain points. Key topics include pricing, product selection, delivery speed, profitability, and customer experience. We tackle these issues by building novel econometric models, machine learning systems, and high-impact experiments which we integrate into business, financial, and system-level decision making. Our work is highly collaborative and we regularly partner with EU- and US-based interdisciplinary teams. We are looking for a Senior Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. If you have an entrepreneurial spirit, you know how to deliver results fast, and you have a deeply quantitative, highly innovative approach to solving problems, and long for the opportunity to build pioneering solutions to challenging problems, we want to talk to you. Key job responsibilities - Provide data-driven guidance and recommendations on strategic questions facing the EU Retail leadership - Scope, design and implement version-zero (V0) models and experiments to kickstart new initiatives, thinking, and drive system-level changes across Amazon - Build a long-term research agenda to understand, break down, and tackle the most stubborn and ambiguous business challenges - Influence business leaders and work closely with other scientists at Amazon to deliver measurable progress and change We are open to hiring candidates to work out of one of the following locations: London, GBR