Zappos Data Scientist Iii, 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. You will work with Zappos' Senior leadership team to solve complex data challenges through advanced analytics and machine learning – creating innovative solutions and influencing product decisions through data-driven insights. You will lead critical initiatives to reduce catalog errors, accelerate product data capture, and develop state-of-the-art image classification systems for fashion features. You will partner daily with engineering teams and business stakeholders to provide expert guidance on model selection and implementation. As a member of the Zappos technical staff, you will leverage machine learning technologies and have access to industry leaders in AI/ML and E-Commerce to help grow your expertise. You will also routinely collaborate with data science teams across our sister companies at Amazon.com and Shopbop.com. You will push the boundaries of what's possible with applied machine learning and bring innovative solutions to bear for customers (including computer vision, NLP, and advanced ML models). You will think big about how data science can transform our catalog operations and be persistent in delivering robust, scalable solutions.Key job responsibilitiesDesign 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.A day in the lifeYou start the day model performance metrics, noting some 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. In the afternoon, you meet with engineering teams 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.About the teamZappos/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.Basic Qualifications5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience4+ years of data scientist experienceExperience with statistical models e.g. multinomial logistic regressionBachelor's degreePreferred Qualifications2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experienceExperience managing data pipelinesExperience as a leader and mentor on a data science teamAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.Posted: September 17, **** (Updated about 1 month ago)Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.#J-*****-Ljbffr