The Causal Machine Learning (CML) team within Amazon's Supply Chain Optimization Technology (SCOT) organization is looking for an experienced and motivated Sr. Manager, Economist to work on exciting and challenging problems related to Amazon's supply chain strategy. Our team provides unique opportunities to both build and see the direct impact of your work on billion-dollar decisions, in one of the world's most advanced supply chains, at massive scale.Your work will help Amazon provide the best customer experience on inventory availability, selection and delivery speed worldwide. You will lead a team that builds large-scale econometric and machine learning systems using world-class data systems and state-of-the-art cloud computing technologies, and whose results are relied upon for selection, buying, removals, and delivery speed decisions, among others. You will lead Amazon's supply chain's experimentation platform and help shape our experimental strategy. You will partner with some of the brightest economists, applied scientists, research scientists, and software engineers to address high-impact business problems and contribute to the design of automated systems with global reach.Your work will have high impact and visibility. You will work closely with stakeholder teams across Amazon to develop science that solves our most important business challenges. You will communicate with and evangelize leaders in various organizations, clearly communicating scientific approaches and findings to business leaders, listening to and incorporating their feedback, and delivering successful scientific solutions. You will lead the vision for the development of scientific models, automated evaluation systems, and experimentation.Key job responsibilities- Work closely with product, business and engineering teams to set the vision and roadmap for your team.- Lead scientists and engineers in the development of innovative econometric and machine learning algorithms, and their deployment in production systems.- Represent your business and operations to executive leadership across functions.- Identify new modeling opportunities, and make business cases for resources to pursue the best of them.- Hire, develop, and retain top science, engineering, and analytical talent.We are open to hiring candidates to work out of one of the following locations:Bellevue, WA, USA- PhD in Economics or closely related field.- 7+ years of experience in solving complex problems in the area of Causal Inference, Forecasting, Optimization or similar disciplines, and developing strategies for large-scale systems.- 4+ years managing science teams, hiring and developing science talent within teams focused on quantitative methods in econometrics, statistical learning, or machine learning.- 10+ years of hands-on experience applying theoretical models in an applied environment.- Significant peer-reviewed scientific contributions in premier journals and conferences.- Proven ability to manage competing priorities simultaneously and driving projects to completion.- Strong interpersonal and written communication skills, along with ability to explain complex technical concepts and analysis implications clearly across different (non-tech) audiences and varying levels of the organization.- Proven track record of driving large scale business results via the application of statistical models.- Proven ability to lead a cross-functional team.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $166,700/year in our lowest geographic market up to $324,100/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on