Catalog Operations Analyst II

This is a fully remote position, open to applicants in Canada.

📋 Description

• Take ownership of data quality results for the Health and Meals sector by establishing goals for accuracy and coverage of essential attributes (such as nutrition, dietary tags, allergens, and preparation/meal context) and driving measurable enhancements across the catalog.

• Design, test, and implement LLM pipelines in collaboration with Catalog Engineering and ML, which include prompt iterations, evaluation frameworks, and human-in-the-loop QA processes.

• Create comprehensive SQL analyses to monitor the health of the catalog, identify root causes, prioritize solutions, and communicate performance and impact to cross-functional stakeholders.

• Establish and continuously improve taxonomies, attribute definitions, and normalization standards; develop SOPs and quality guidelines that can be scaled across internal teams, external content providers, and BPOs.

• Oversee daily operations with external vendors and data partners (such as BPOs), setting SLAs, creating QA workflows, and implementing sampling plans that enhance precision and recall at scale.

• Collaborate with Product, DS, and XFN teams to define experiments, validate assumptions, and translate insights into roadmaps that enhance discovery, search relevance, and conversion for health and meal-related use cases.

⛳️ Requirements

• A minimum of 3 years of experience in catalog/content operations, data operations, or data quality within an e-commerce, marketplace, retail, or similar high-scale data environment.

• A Bachelor’s degree in a quantitative, analytical, or related field (such as Data/Information Science, Business, Economics, Statistics) or equivalent practical experience.

• Proven success in partnering with Engineering, Data Science, and Product teams to define requirements and deliver production-scale projects.

• Skilled in SQL (including joins, aggregations, and window functions) and advanced Excel/Google Sheets for analysis, QA sampling, and reporting.

• Understanding of LLMs and prompt design for data extraction, classification, or attribute enrichment, including LLM evaluation and feedback loops.

• Practical experience in defining and managing data quality metrics (such as accuracy, precision, recall) and conducting root cause analyses.

• Experience in operationalizing workflows with external vendors/BPOs or data providers, including SOPs, SLAs, and multi-step QA processes.

🏝️ Benefits

• Highly competitive market compensation

• New hire equity grant

• Annual refresh grants