Amazon's Supply Chain Optimization (SCOT) group is looking for an Applied Scientist to optimize one of the most complex logistics systems in the world. Academic and/or practical background in Machine Learning, Operations Research, Systems Engineering and Optimization, or Process Control are particularly relevant for this position. Experience in model-based engineering and/or multidisciplinary analysis & optimization is also a plus.
Amazon's extensive logistics system comprises thousands of fixed infrastructure nodes with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements truly unparalleled. This magnificent challenge is a terrific opportunity to understand, model, simulate, optimize, and reshape one of the world's most complex systems.
You will make the real complexity of our logistics system visible, tangible, and manageable using cutting edge analytical methods. You will use modeling and simulation to validate assumptions on the intricate interactions among different elements of our system. You will identify and evaluate opportunities to improve customer experience, network speed, cost, and the efficiency of capital investment. You will develop system components using optimization, simulation, and machine learning techniques. You will quantify the improvements resulting from the application of these tools and you will evaluate trade-offs between competing outputs of the system.
This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-technical audiences, and close partnership with many stakeholders from operations, finance, IT, and business leadership.
Amazon is a company operating a marketplace for consumers, sellers, and content creators.