Data Scientist, Spx AI Lab, Spx Science

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

Data Scientist to build and launch production-grade agentic capabilities for Amazon Seller Assistant, a multi-agent GenAI system. Responsibilities include analyzing seller pain points, designing measurement frameworks, applying NLP and statistical modeling, and collaborating with cross-functional teams to improve the seller experience at Amazon's scale.

What you'd actually do

  1. Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
  2. Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
  3. Design and execute robust causal inference and measurement frameworks, including A/B testing, quasi-experiments, and observational causal methods (e.g., diff-in-diff, synthetic control, propensity score methods).
  4. Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
  5. Apply NLP and statistical modeling techniques—including topic modeling, clustering, semantic similarity, and classification—to uncover insights from unstructured seller interactions, feedback, and content.

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

  • multi-agent system
  • agentic capabilities
  • production-grade
  • Amazon's scale
  • rigorous measurement

Other signals

  • multi-agent system
  • agentic capabilities
  • production-grade
  • Amazon's scale