The Selling Partner Experience (SPX) organization strives to make Amazon the best place for Selling Partners to do business by building AI capabilities powering the Selling Assistant, a conversational assistant experience for Selling Partners.
Requirements
- 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
- Knowledge of machine learning concepts and their application to reasoning and problem-solving
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Responsibilities
- 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.
Other
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
- Experience effectively communicating complex concepts through written and verbal communication
- Ability to work on multi-team, cross-disciplinary projects
- Ability to deliver results for customers in an inclusive culture
- Must be willing to apply for and obtain any necessary clearance
