Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Amazon's Middle Mile Science group is seeking a Senior Applied Scientist to develop advanced machine learning and optimization models supporting pricing and revenue management for its external freight business. This role involves creating novel forecasting and dynamic pricing models, applying causal inference and artificial intelligence techniques to enhance marketplace services and execution for customers. The Middle Mile Science team builds optimization and machine learning systems powering Amazon's freight transportation network, covering network design, pricing, real-time load planning, and capacity utilization. The role requires innovation to address unique business challenges and involves close collaboration with business leaders, engineers, and other scientists to design scalable products across multiple transportation modes. You will prototype new learning algorithms, conduct experiments, and present research findings to senior leadership. Your work will influence algorithm design, model structure, efficiency, and integration across Amazon's product portfolio.

About the Team
The Middle Mile Marketplace Science team develops algorithms for Amazon's growing freight marketplace, which contracts with third-party shippers and independent carriers under various contract structures. The team focuses on optimizing pricing and matching mechanisms to improve the experience for carriers and shippers, tackling complex problems with significant business impact.

Experience
- 5+ years building machine learning models or developing algorithms for business applications
- Proficient programming skills in Java, C++, Python or related languages
- Strong foundation in computer science fundamentals including object-oriented design, data structures, algorithm design, problem solving, and complexity analysis

About You
- Passionate about innovation and solving complex problems in large-scale systems
- Collaborative team player able to work closely with cross-functional teams including business leaders and engineers
- Effective communicator with experience presenting research findings to senior leadership

Qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field, or Master's degree with 10+ years of industry or academic research experience
- Preferred experience with deep learning frameworks such as MxNet and TensorFlow
- Hands-on experience with reinforcement learning and/or dynamic programming
- Experience working with AWS technologies
- Experience applying causal inference and experimental design to drive business decisions in large-scale systems
- Significant peer-reviewed scientific contributions in premier journals and conferences