Catalog Operations Analyst II

Overview

Instacart’s Catalog Operations team powers the data that makes shopping effortless. Catalog data represents the vast majority of what customers see when they browse, search, and buy. Our quality, coverage, and accuracy directly shape the customer experience. We are an AI-first operations team that builds LLM-driven pipelines and scalable quality programs to create, enrich, and govern product data across the Instacart ecosystem.

We’re looking for a Catalog Operations Analyst II to accelerate our Health and Meals pillar within Online Grocery, one of our top strategic priorities. In this role, you will drive end-to-end data quality and enrichment for health, nutrition, and meal-related attributes, partnering closely with Catalog Engineering, Data Science, Product, and ML, as well as external data providers and BPOs. You’ll join a tight-knit team of 8 who roll up their sleeves, solve creatively, and deliver measurable impact at scale.

This role is based in Canada and is remote-eligible nationwide, with a preference for candidates located in Ontario (ideally Greater Toronto Area) for periodic in-person collaboration.

About the Job

• Own data quality outcomes for the Health and Meals pillar by defining accuracy and coverage goals for critical attributes (e.g., nutrition, dietary tags, allergens, preparation/meal context) and driving measurable improvements across the catalog.
• Design, test, and operationalize LLM pipelines in partnership with Catalog Engineering and ML, including prompt iterations, evaluation frameworks, and human-in-the-loop QA.
• Develop robust SQL analyses to monitor health of the catalog, identify root causes, prioritize fixes, and communicate performance and impact to cross-functional stakeholders.
• Establish and continuously refine taxonomies, attribute definitions, and normalization standards; author SOPs and quality guidelines that scale across internal teams, external content providers, and BPOs.
• Manage day-to-day execution with external vendors and data partners (e.g. BPOs), setting SLAs, creating QA workflows, and implementing sampling plans that improve precision and recall at scale.
• Partner with Product, DS, and XFN teams to scope experiments, validate assumptions, and translate insights into roadmaps that elevate discovery, search relevance, and conversion for health and meal oriented use cases.

This is a fast-paced, evolving environment. You’ll thrive if you enjoy ambiguity, take ownership from problem definition through execution, and communicate clearly to align diverse partners on outcomes.

About You

Minimum Qualifications

• 3+ years of experience in catalog/content operations, data operations, or data quality within e-commerce, marketplace, retail, or a similar high-scale data environment.
• Bachelor’s degree in a quantitative, analytical, or related field (e.g., Data/Information Science, Business, Economics, Statistics) or equivalent practical experience.
• Demonstrated success partnering with Engineering, Data Science, and Product to scope requirements and deliver production-scale projects.
• Proficiency in SQL (including joins, aggregations, and window functions) and advanced Excel/Google Sheets for analysis, QA sampling, and reporting.
• Familiarity with LLMs and prompt design for data extraction, classification, or attribute enrichment, including LLM evaluation and feedback loops.
• Hands-on experience defining and managing data quality metrics (e.g., accuracy, precision, recall) and running root cause analyses.
• Experience operationalizing workflows with external vendors/BPOs or data providers, including SOPs, SLAs, and multi-step QA processes.

Preferred Qualifications

• Experience using AI tools (e.g. Claude Code, Codex) in your day to day.
• Experience with data wrangling, QA automation, and scaling manual processes.
• Experience building dashboards in Looker, Tableau, or Mode to track operational and quality KPIs.
• Track record of delivering results in dynamic, ambiguous environments while communicating effectively with technical and non-technical audiences.
• Background in ecommerce, grocery/CPG data, or technology/startups.

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