Applied Scientist

About the Role

The Amazon Transportation Services, North America Sort Center Science team is looking for an enthusiastic, customer-obsessed Applied Scientist. This role focuses on managing the delivery of millions of products weekly, achieving on-time delivery cost-effectively, and developing scalable processes and tools. The individual will own business challenges, make data-driven decisions, and influence change across the organization, impacting customer experience and middle mile network operations.

Key Responsibilities

• Design and develop advanced mathematical optimization and machine learning solutions in the domains of network design and optimization.
• Research, prototype, simulate, and experiment with models using programming languages such as Java and Python; participate in production-level deployment.
• Create, enhance, and maintain technical documentation and science designs.
• Present to other Scientists, Product, and Software Engineering teams, as well as Stakeholders.
• Lead project plans from a scientific perspective by managing product features, technical risks, milestones, and launch plans.

Requirements & Tech Stack

• Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field.
• Experience programming in Java, C++, Python, or a related language.
• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse.
• Experience implementing algorithms using both toolkits and self-developed code.
• Publications at top-tier peer-reviewed conferences or journals.

Qualifications

• Strong scientific thinking.
• Good software and statistics experience.
• Skills to help manage projects and operations, improve metrics, and develop scalable processes and tools.
• History of operations research, machine learning, and the ability to use data and research to make changes.
• Robust skills in research and implementation of scalable products and models.
• Ability to work with a team and make decisions independently in ambiguous environments.
• Ideal candidates will be high potential, strategic, and analytic graduates with a PhD in Operations Research, Statistics, Engineering, and Supply Chain.