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Applied Scientist, Middle Mile Marketplace Science

Job ID: 1884766 | Services LLC


Job summary
Amazon is looking for a motivated and innovative Applied Scientist with strong analytical skills and practical experience to join our Middle Mile Marketplace Science team, part of our Middle Mile Planning Research and Science (mmPROS) organization. We are hiring specialists with expertise in machine learning, operations research, systems engineering, optimization and modeling applied to logistics planning and optimization, marketplace engineering, pricing and revenue management.

Middle Mile Air and Ground represents one of the fastest growing logistics areas within Amazon. Amazon Transportation Services transports millions of packages via air and ground and continues to grow year over year. Our organization, mmPROS, is charged with developing science strategy, models, algorithms, analysis for Amazon Transportation Services. The Middle Mile Marketplace Science team is responsible for the science behind Amazon’s dynamic two-sided marketplace within the transportation space and the underlying algorithms needed to efficiently match available capacity provided by tens of thousands of independent carriers with both internal and external demand, and to manage real-time spot pricing and contract pricing in this setting. These algorithms rely heavily on the latest advances in optimization, machine learning, stochastic modeling, and marketplace engineering. In addition, Amazon often finds existing techniques do not effectively match our unique business needs which necessitates the innovation and development of new approaches and algorithms to find an adequate solution.

As an Applied Scientist responsible for middle mile, you will be working in a highly collaborative environment partnering with various science, product management, engineering, operations, finance, business intelligence and analytics teams to develop to design and build scalable products operating across multiple modes. You will create experiments and prototype implementations of new algorithms and prediction techniques. You will have exposure to top level leadership to present findings of your research. You will also work closely with other scientists and also engineers to implement your models within our production system. You will implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility, and make decisions that affect the way we build and integrate algorithms across our product portfolio.

An ideal candidate will be an expert in the areas of operations research, machine learning, or and statistics, with expertise in applying theoretical models in an applied environment. Challenges will involve dealing with very large data sets, and developing practical, scalable models.


· Experience building machine learning models or developing algorithms for business application.
· 1+ years of experience programming in Java, C++, Python or related language
· PhD (OR Master's Degree plus 10+ years of industry or academic research experience) in Engineering, Technology, Computer Science, Machine Learning, Robotics, Operations Research, Statistics, Mathematics or a related quantitative field
• Proficiency in model development, model validation and model implementation for applications
• Ability to convey mathematical results to non-science stakeholders
• Strength in clarifying and formalizing complex problems
• Superior verbal and written communication and presentation skills,
• Ability to convey rigorous mathematical concepts


• PhD and 5+ years of academic or industry applied research experience.
• 2+ years of practical experience applying modeling to solve complex problems in an applied environment.
• Hands-on experience with pricing and revenue management techniques and algorithms
• Significant peer-reviewed scientific contributions in premier journals and conferences.
• Experience in data mining and using databases in a business environment with, complex datasets.
• Experience working with AWS technologies.
• Strong personal interest in, researching, and creating new technologies with high customer impact.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit