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 and 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
▪ PhD degree in Computer Science, Machine Learning, Applied Mathematics, Operations Research or a related field, or a Master's degree and at least 3 years of relevant work experience ▪ Experience in designing analytic and/or algorithmic solutions to business or operational problems ▪ Experience implementing algorithms, tailored to particular business needs and tested on large data sets ▪ Experience with scripting languages (Python, Ruby, etc.), SQL and Statistical tools, and object-oriented programming languages (Java, C++, etc.) ▪ Excellent communication skills with both technical and non-technical