Senior Applied Scientist, Agentic AI for Data Analytics and Science, Speed Analytics and Science

Senior Applied Scientist

Are you excited by the opportunity to define how Amazon builds and scales intelligent AI systems that influence strategic decisions across a massive transportation network? Do you want to lead the development of agentic AI solutions and mentor the next generation of scientists while shaping how we use generative AI at scale?

Amazon's North American Transportation Data Science & Analytics team is looking for a Senior Applied Scientist to lead the design and implementation of agentic AI systems that simulate, reason, and deliver insights across Amazon's dynamic supply chain and delivery operations. You will set scientific direction, define development strategy, and lead by examplebuilding intelligent agents that accelerate our ability to analyze complex data and make customer-centric decisions at scale.

This is a high-impact, highly visible role. You'll collaborate closely with product, engineering, science, and business leaders across planning, forecasting, operations, and last-mile delivery. Delivery speed is one of Amazon's core customer value propositions and a key differentiatoryour work will directly shape how we measure and improve that experience.

Key job responsibilities:

• Define the AI and agentic development strategy for transportation analytics, including use case prioritization, architecture principles, and integration frameworks
• Lead the design and development of autonomous AI agents that deliver insights, simulate system behavior, and support experimentation across analytics workflows
• Build systems that allow agents to interact with APIs, knowledge bases, structured and unstructured data sources
• Mentor and develop junior scientists and engineers, providing scientific guidance, code reviews, and career development support
• Collaborate with Data Scientists, BIEs, and Engineering teams to integrate agentic systems into production workflows and internal tools
• Define and own agent evaluation frameworksmeasuring business impact, correctness, and efficiency at scale
• Drive adoption of shared infrastructure like reusable APIs, prompt libraries, and model registries
• Partner with AWS teams and internal technical stakeholders to leverage emerging AI/ML technologies, and serve as an evangelist for scalable, interoperable solutions
• Influence cross-org discussions on AI strategy, experimentation tooling, and reusable architecture to support Amazon-wide analytics goals

About the team:

We enable data-driven decision-making for Amazon's North American Transportation network by combining deep analytics, causal modeling, and experimentation. Our team supports business and tech stakeholders across planning, delivery, and customer experience by developing scalable tools, dashboards, and metrics. As we evolve toward agentic and generative AI, we are reimagining how insights are producedmoving from static reports to intelligent, autonomous systems that proactively surface opportunities and drive operational excellence.