Location
London

Hours
Full Time

Salary
Competitive, commensurate with experience

About the Role
Amazon's Middle Mile Science group is seeking an Applied Scientist to develop machine learning and optimization models for large-scale transportation planning systems. This role focuses on building dynamic pricing and network planning models to enhance operations and services for Amazon's external freight customers. The Middle Mile Science team creates optimization and machine learning systems that power Amazon's freight transportation network, covering network design, pricing, real-time load planning, and capacity utilization. Given the scale of Amazon's fulfillment operations, robust transportation networks are essential to minimize costs while meeting customer deadlines. Real-time execution relies on advanced 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 innovates new approaches and algorithms to address unique business challenges. As an Applied Scientist focused on external freight within middle mile transportation, you will collaborate closely with business leaders, engineers, and fellow scientists to design and build scalable products across multiple transportation modes. You will create experiments and prototypes of new machine learning and optimization applications, present research findings to senior leadership, and implement models within production systems. Writing production-quality, scalable, and maintainable code is a key responsibility, along with making decisions that influence how algorithms are integrated across Amazon's product portfolio.

About the Team
The Middle Mile Marketplace Science team develops algorithms for Amazon's rapidly growing freight marketplace. Amazon contracts with third-party shippers and a network of independent carriers, using various contract structures with differing service and risk profiles. The team focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, continually improving the experience for carriers and shippers. This area presents many challenging problems with significant business impact for Amazon.

Experience
- Programming experience in Java, C++, Python, or related languages
- Experience with discrete and continuous optimization methodologies and algorithms
- 3+ years of building machine learning or optimization algorithms for business applications

About You
- Strong analytical and problem-solving skills
- Ability to work collaboratively with cross-functional teams including business leaders, engineers, and scientists
- Passion for innovation and developing scalable solutions in a fast-paced environment

Qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field, or Master's degree with 5+ years of industry or academic research experience
- Preferred: Experience in professional software development
- Preferred: Familiarity with standard machine learning and statistical modeling tools and techniques such as random forests, gradient-boosted regression, LASSO, logistic regression
- Preferred: Strong track record of publications at top-tier journals or conferences
- Preferred: Experience with integer programming, dynamic programming, and/or stochastic optimization