Description
Amazon’s Middle Mile Science group is looking for a Senior Applied Scientist to build machine learning and optimization models to support pricing and revenue management of its external freight business. This includes the development of novel forecasting and dynamic pricing models, as well as the application of causal inference and artificial intelligence techniques, to improve marketplace services and execution for our customers.
About the Middle Mile Science Group
The Middle Mile Science group develops optimization and machine learning systems that power Amazon's freight transportation network, from network design and pricing to real-time load planning and capacity utilization. The scale of Amazon’s fulfillment operations requires robust transportation networks that minimize cost while meeting all customer deadlines. Real‑time execution depends on state‑of‑the‑art optimization and artificial intelligence to coordinate thousands of operators and drivers. This includes shipper‑facing and carrier‑facing marketplace algorithms as well as network planning and optimization tools. Amazon often finds that existing techniques do not match its unique business needs, driving the innovation of new approaches and algorithms.
Key Responsibilities
As a Sr. Applied Scientist responsible for middle mile transportation, you will work closely with business leaders and engineers to design and build scalable products across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques, presenting findings to top‑level leadership. You will work closely with other scientists and engineers to implement your models within the production system, ensuring solutions are exemplary in algorithm design, clarity, model structure, efficiency, and extensibility, and making decisions that affect how we build and integrate algorithms across our product portfolio.
About The Team
Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, continually improving the experience for carriers and shippers.
Basic Qualifications
- 5+ years of building machine learning models or developing algorithms for business applications
- 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)
Preferred Qualifications
- 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
Equal‑Opportunity Employer
Amazon is an equal opportunities employer. It does not discriminate on the basis of protected veteran status, disability, or other legally protected status. We value a diverse workforce and prioritize privacy and security of our candidate data.
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Amazon’s Middle Mile Science group is looking for a Senior Applied Scientist to build machine learning and optimization models to support pricing and revenue management of its external freight business. This includes the development of novel forecasting and dynamic pricing models, as well as the application of causal inference and artificial intelligence techniques, to improve marketplace services and execution for our customers.
About the Middle Mile Science Group
The Middle Mile Science group develops optimization and machine learning systems that power Amazon’s freight transportation network, from network design and pricing to real-time load planning and capacity utilization. The scale of Amazon’s fulfillment operations requires robust transportation networks that minimize cost while meeting all customer deadlines. Real‑time execution depends on state‑of‑the‑art optimization and artificial intelligence to coordinate thousands of operators and drivers. This includes shipper‑facing and carrier‑facing marketplace algorithms as well as network planning and optimization tools. Amazon often finds that existing techniques do not match its unique business needs, driving the innovation of new approaches and algorithms.
Key Responsibilities
As a Sr. Applied Scientist responsible for middle mile transportation, you will work closely with business leaders and engineers to design and build scalable products across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques, presenting findings to top‑level leadership. You will work closely with other scientists and engineers to implement your models within the production system, ensuring solutions are exemplary in algorithm design, clarity, model structure, efficiency, and extensibility, and making decisions that affect how we build and integrate algorithms across our product portfolio.
About The Team
Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, continually improving the experience for carriers and shippers.
Basic Qualifications
- 5+ years of building machine learning models or developing algorithms for business applications
- 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)
Preferred Qualifications
- 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
Equal‑Opportunity Employer
Amazon is an equal opportunities employer. It does not discriminate on the basis of protected veteran status, disability, or other legally protected status. We value a diverse workforce and prioritize privacy and security of our candidate data.
#J-18808-Ljbffr…