About the job
Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow. Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Data Scientist to help define and build the next generation of Amazon Seller Assistant. You will partner with top-tier scientists, product managers and engineers to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on.
Responsibilities
Respond to Seller feedback and implement fix in Gen AI solution to enhance Seller experience
Drive deep-dive analytical studies to understand seller pain points, evaluate feature performance, and identify opportunities to improve the Selling Partner experience.
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).
Develop scalable analytical pipelines for impact measurement, KPI development, metric integrity validation, and long-term business monitoring.
Apply NLP and statistical modeling techniques—including topic modeling, clustering, semantic similarity, and classification—to uncover insights from unstructured seller interactions, feedback, and content.
Partner with scientists, engineers, economists, and product managers to translate ambiguous problems into structured analytical approaches and influence product roadmaps with data-driven recommendations.
Build and maintain automated analytics tools and dashboards to democratize insights for product, science, and engineering teams.
Collaborate scientists to evaluate model-driven features, quantify impact, and ensure mechanisms are grounded in rigorous measurement.
Research and experiment with new analytical and measurement methodologies, ensuring Amazon leverages the latest best practices in causal inference, NLP, and GenAI.
Qualifications
Minimum
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)
Preferred
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