Zappos Data Scientist II, Zappos​/Shopbop Catalog Engineering

As a Data Scientist on the Shopbop/Zappos Catalog Tech team, you will design and implement scientific approaches to revolutionize how we manage and enhance our product catalog data for our world‑class selection of Shoes, Kids, and Active wear.

• Design and implement machine learning approaches to improve catalog data quality.
• Develop and validate scientific methodologies for automated data capture and classification.
• Partner with engineering teams to integrate ML models into production systems.
• Create and present analysis that drives decision‑making at the senior leadership level.

You start the day reviewing model performance metrics, noting drift in the image classification system that needs investigation. You spend the morning developing a new approach to reduce product attribute errors using recent advances in LLMs, then meet with engineering teams in the afternoon to advise on model architecture for a new feature, and wrap up by analyzing the results of your latest A/B test on data capture efficiency improvements.

Zappos/Shopbop Catalog Tech team owns the software that drives our photostudio, product cataloging, and integration to Amazon’s marketplace. We use Amazon’s Leadership Principles and Engineering Expertise but have our own fun vibe. We are located in Madison, WI, and Las Vegas, NV.

• 2+ years of data scientist experience.
• 3+ years of experience with data querying languages (e.g., SQL), scripting languages (e.g., Python) or statistical/mathematical software (e.g., R, SAS, Matlab, etc.).
• 3+ years of experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance.
• 1+ year of guiding and coaching a group of researchers.
• 1+ year of working with or evaluating AI systems.
• 1+ year of creating or contributing to mathematical textbooks, research papers, or educational content.
• Master’s degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in STEM.
• Experience applying theoretical models in an applied environment.

• Ph.D. in Science, Technology, Engineering, or Mathematics (STEM).
• Knowledge of machine learning concepts and their application to reasoning and problem‑solving.
• Experience in Python, Perl, or another scripting language.
• Experience in an 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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.