Economist

Job summary Are you excited about powering Amazon’s expansion through economic models? Do you thrive in a fast-moving, innovative environment that values data-driven decision making and sound scientific practices? We are looking for PhD Economists to build the next level of economic models that will help Amazon grow and succeed. This role will focus on expanding our reach to analyze various fulfillment options for Amazon's network worldwide. You will have a proven track-record of delivering measurable benefit to business through econometric models, strategic analysis and model building. You will be comfortable handling complex economic problems and making the right modeling tradeoffs by applying strong economic reasoning. You will be able to break down complex information and insights into clear and concise language and be comfortable presenting your findings to audiences with a broad range of backgrounds. Key job responsibilities As an economist, you will work with other scientists, product managers, software engineers, and business intelligence engineers to help deliver forecasting and decision support models leveraging econometric, statistical and ML techniques. The models you develop will drive changes in transportation and fulfillment networks to ensure we’re providing customers with the fastest delivery experience while optimizing costs. You will be expected to own the development of econometric models and to manage the modelling and validation work for your analysis, and working with SDEs to integrate the models into production systems. About the team SCOT Network Topology science team focuses on research areas and tools that determine Amazon outbound network design as we transition to relying on our internal carrier network and accelerate one-day delivery speed. There are various strategic questions the team is attempting to answer, such as: what is the impact of placement on outbound cost and delivery speed? What is the optimal network design given capacity constraints? How can we forecast accurately fulfillment pattern for different customer clusters? In addition to network, we also use and techniques to evaluate new facilities recommendation for long term estimates. We use to approximate the network, and simulation of how our choices will perform. Our team is responsible for building the core intelligence, insights, and algorithms that support the real estate acquisition strategies for Amazon physical stores. If you are interested in diving into a multi-discipline, high impact space this team is for you. The team is a mixture of Research/Applied Scientists, Software Engineers, Business Intelligence Engineers and Product Managers. To help describe some of our challenges, we created a short video about at Amazon - http://bit.ly/amazon-scot