Sr. Applied Scientist, Amazon Transportation

## Responsibilities - Build machine learning and optimization models to support pricing and revenue management of Amazon's external freight business. - Develop novel forecasting and dynamic pricing models. - Apply causal inference and artificial intelligence techniques to improve marketplace services and execution for customers. - Work closely with business leaders and engineers to design and build scalable products across multiple transportation modes. - Create experiments and prototype implementations of new learning algorithms and prediction techniques. - Present findings to top-level leadership. - Collaborate with other scientists and engineers to implement models within production systems. - Implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. - Make decisions that affect the way algorithms are built and integrated across the product portfolio. ## Requirements - 5+ years of building machine learning models or developing algorithms for business application experience. - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field, or Master's degree and 10+ years of industry or academic research experience. - Experience programming in Java, C++, Python, or related language. - Experience in computer science fundamentals (object-oriented design, data structures, algorithm design, problem solving, and complexity analysis). ## Nice to Have - Experience with popular deep learning frameworks such as MxNet and TensorFlow. - Significant peer-reviewed scientific contributions in premier journals and conferences. - Hands-on experience with reinforcement learning and/or dynamic programming. - Experience working with AWS technologies. - Experience applying causal inference and/or experimental design to drive business decisions in large-scale systems. ## About the Team - The Middle Mile Marketplace Science team builds algorithms for Amazon’s rapidly growing freight marketplace. - Amazon contracts with third-party shippers and a network of independent carriers using a mix of contract structures with varying service and risk profiles. - The work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, continually improving the experience for carriers and shippers. ## Benefits - Amazon is an equal opportunities employer. - The company values diversity and makes recruiting decisions based on experience and skills. - Privacy and data security are top priorities. - The company provides accommodations for candidates with disabilities during the application and hiring process.