Data Scientist, Spx AI Lab, Spx Science

Amazon Amazon · Big Tech · Seattle, WA · Data Science

The Data Scientist will help define and build the next generation of Amazon Seller Assistant, a GenAI-first, multi-agent system. The role involves owning product vision, strategy, and roadmap for agentic capabilities, including reasoning, planning, memory, and context engineering. The scientist will translate AI research into production features, design evaluation frameworks, analyze seller data, and drive cross-functional alignment to deliver agentic experiences at Amazon's scale.

What you'd actually do

  1. Own the product vision, strategy, and roadmap for a key Seller Assistant capability area.
  2. Define and ship agentic experiences — reasoning, planning, memory, context engineering — that solve hard seller problems at scale.
  3. Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on.
  4. Design rigorous evaluation frameworks — automated and human-in-the-loop — to measure agent quality, accuracy, and business impact.
  5. Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team.

Skills

Required

  • 2+ years of data scientist experience
  • 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • 1+ years of working with or evaluating AI systems experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Nice to have

  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in a ML or data scientist role with a large technology company
  • Experience in defining and creating benchmarks for assessing GenAI model performance
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication

What the JD emphasized

  • production-grade agentic capabilities at Amazon's scale
  • Define and ship agentic experiences
  • Design rigorous evaluation frameworks
  • shipping production-grade, multi-agent systems

Other signals

  • GenAI-first, multi-agent system
  • production-grade agentic capabilities at Amazon's scale
  • shipping production-grade, multi-agent systems