E Commerce Data Associate

Benefits:

• Health insurance
• Paid time off
• Vision insurance
• 401(k)
• 401(k) matching
• Dental insurance

E-Commerce Data Associate

Department: E-Commerce / Digital

About the Role

The Commerce Data Associate is an entry-level role built for a smart, analytical recent graduate — some work experience is welcome but not required. You’ll help us test and learn our way through our catalog: experimenting with how product and category data is structured, analyzing what improves search, navigation, and SEO performance, and applying those learnings at scale. Your work will directly shape the development of new online features — the data you structure is what powers them. We’ll train you on the tools and the domain; you bring curiosity, analytical horsepower, and the drive to take our vision and chart a path to achieve it.

Key Responsibilities

• Structure, enrich, and clean up e-commerce data across the catalog

• Drive a test-and-learn approach: help design and run experiments on data structure (categorization, attributes, naming) and analyze the results

• Work with the product data team to maintain product records — supporting updates to attributes, specifications, descriptions, categorization, and cross-references

• Audit existing data for gaps, inconsistencies, and errors; identify patterns and flag systemic issues

• Use analytics and search data to understand how customers interact with the catalog and where data improvements will matter most

• Support new product onboarding and bulk data loads

• Prepare and validate the data behind new online features and functionality ahead of launch, partnering with the development team as features take shape

• Document processes and learnings; contribute to improving data workflows

What We’re Looking For

• Recent college graduate with a bachelor’s degree in a relevant field (e.g., business, marketing, data analytics, information systems, economics, or similar)

• Smart and analytical: you enjoy digging into data, spotting patterns, and forming hypotheses about what will work

• A test-and-learn mindset — comfortable trying things, measuring outcomes, and iterating rather than expecting a fixed playbook

• Proficient in Excel, with a willingness to master new tools; existing comfort with data analysis is a bonus

• Strong attention to detail and consistency; comfortable with high-accuracy work