$ cat jobs/product-operations-analyst-l2-commerceiq-ccb9289c5f91.json
Product Operations Analyst - L2
The Company CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week. 2,200+ Customers 10 of Top 12 CPG Companies 900+ Retailers Connected $200M+ Raised Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO. Key Responsibilities Own day-to-day product operations activities including change management requests, product maintenance, product tagging, banner tagging, PIM matching, and configuration updates across customer accounts. Ensure high levels of data quality and operational excellence by validating product classifications, taxonomy mappings, catalog configurations, and onboarding-related deliverables. Investigate operational issues, identify root causes, and work cross- functionally with Product, Engineering, Data Science, and Customer Success teams to drive timely resolution and long-term fixes. Analyze operational workflows, identify bottlenecks and inefficiencies, and recommend process improvements that improve accuracy, scalability, and turnaround times. Drive automation and AI-assisted workflow initiatives by helping translate manual processes into scalable systems, business rules, and operational playbooks. Support strategic and operational initiatives across the organization, taking ownership of new programs, process rollouts, and continuous improvement efforts as business needs evolve. Required Qualifications 3–5 years of experience in Operations, Product Operations, Data Operations, Business Operations, Catalog Operations, or Analytics Strong analytical and problem-solving abilities Hands-on SQL experience Advanced Excel / Google Sheets skills Experience working with large datasets and operational workflows Strong
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