Research Scientist, Selling Partner Experience
About the role
We’re looking for a Research Scientist to join a team that measures and explains how over 2.4 million sellers and vendors experience selling on Amazon. You’ll apply survey science, psychometrics, and applied statistics to help drive meaningful change at Amazon on behalf of Sellers.
Key Job Responsibilities
Apply psychometric and survey methodology techniques (e.g., IRT, factor analysis, scale development, single-item indicators) to measure seller experience constructs with scientific rigor
Contribute to frameworks that link seller attitudinal data to behavioral outcomes and identify high-impact opportunity areas
Design and execute statistical analyses including regression modeling, significance testing, and driver analysis to identify what matters most to sellers
Apply observational causal evaluation methods to estimate the effects of policy changes, product launches, and platform interventions on seller experience
Build and maintain analytical pipelines that transform raw survey data into production-ready metrics, reports, and dashboards
Analyze open-ended survey responses using text classification, thematic coding, and natural language processing techniques
Monitor and improve survey response rates, sampling methodology, and data quality
Productionalize research code: take analyses from prototype to automated, reproducible pipelines that run reliably in production environments
Communicate findings clearly to technical and non-technical audiences through written reports, data visualizations, and presentations
Collaborate with cross-functional partners to translate business questions into well-defined research problems and scientific metrics
Document research methods, assumptions, and limitations transparently to ensure reproducibility
Basic Qualifications
PhD in a quantitative field, or MS degree and 3+ years of quantitative field research experience
Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
Experience with data analysis package (R, SAS, Matlab, etc.)
Experience using SQL databases to manage and analyze large data sets
Experience with lab-based user testing, remote testing, iterative prototype testing, survey design, and usage of multiple methods within a study
Experience applying basic statistical methods (e.g. regression) to difficult business problems
Experience using data visualization tools
Experience with survey research methodology and psychometric measurement (e.g., item response theory, factor analysis, scale construction, reliability analysis) as well as single-item indicators
Preferred Qualifications
Experience in causal modeling like graphical models, causal Bayesian network, potential outcomes, A/B testing, experiments, quasi-experiments, and data science workflows
Knowledge of machine learning processing: computer vision, NLU, NLP or operations research
Experience in performing regression analysis and building classification models using machine learning algorithms
Experience with various types of research methodologies is key, including quant, qual, 1P & 3P data, trend analysis & forecasting, etc.