Group PM - Product Knowledge eBay

About EBay

Job Description

At eBay, the focus is on revolutionizing the way people shop and sell globally. With a presence in over 190 markets, eBay empowers millions of buyers and sellers. The company is dedicated to pushing boundaries and reshaping the future of ecommerce for enthusiasts like you. The customer is at the core of everything eBay does, fostering authenticity, welcoming bold ideas, and encouraging individuality in the workplace. Together, the eBay team is committed to ensuring the future of customers, the company, and the planet. Join a team of passionate thinkers, innovators, and dreamers at eBay. Together, they aim to connect people and build communities to create economic opportunities for all. About The Role: eBay is on a mission to develop the most intelligent and scalable product knowledge system in ecommerce, utilizing AI, structured data, and cutting-edge taxonomy/ontology strategies. The company is seeking a Product Manager who excels in the intersection of structured data, AI/ML, and search optimization. In this role, you will be responsible for owning and expanding the AI-driven product knowledge ecosystem. Your focus will be on enhancing taxonomy, ontology, and catalog data to improve how millions of customers discover products. What You'll Do: - Define & Implement Product Knowledge Strategy: Take charge of the roadmap for taxonomy, ontology, structured data, and knowledge graph initiatives, aligning them with AI/ML and Product teams. - Drive AI-Powered Taxonomy & Ontology Development: Collaborate with data scientists, engineers, and analysts to build, test, and scale ML-driven classification, entity resolution, and knowledge graph models. - Improve Search & Product Discovery: Ensure that structured product data directly enhances search relevance, filtering, and recommendation algorithms. - Develop & Enforce Data Standards: Lead governance for taxonomy updates, structured metadata, and attribute standardization to maintain a scalable and accurate catalog. - Enable LLMs for Product Knowledge: Work with AI teams to develop LLM-powered solutions for automated tagging, classification, and enrichment. - Measure & Iterate: Define key metrics and evaluation frameworks to monitor the impact of structured data improvements on search, recommendations, and personalization. - Deeply Integrate with AI/ML Teams: Collaborate closely with AI, data science, and engineering teams to create scalable, automated solutions for product classification and catalog intelligence. What We're Looking For: - Product Leadership in Data/AI: Minimum of 10 years in product management, preferably in eCommerce, search, recommendations, or AI-driven product knowledge systems. - AI & Data Fluency: Experience with ML models, knowledge graphs, LLMs, and structured data strategies to drive business outcomes. - Taxonomy & Ontology Expertise: Strong understanding of product classification, metadata structuring, and entity resolution techniques. - Search & Discovery Focus: Previous experience optimizing product search, recommendations, and structured navigation. - Technical Comfort: Familiarity with SQL, APIs, data pipelines, and AI/ML workflows. - High-Agency & Execution-Driven: Possess a startup-like attitude with the ability to drive cross-functional alignment, influence without authority, and deliver results rapidly. - Strong Analytical & Communication Skills: Capable of translating data-driven insights into clear product strategies. Why Join Us - Shape the AI-powered future of eCommerce product discovery. - Be at the forefront of AI-driven taxonomy, ontology, and knowledge graph development. - Work within a high-agency, startup-like culture where your decisions directly impact millions of users. - Collaborate with groundbreaking AI/ML teams to redefine structured data for eCommerce. - Drive innovations that enhance search, personalization, selling, and product discovery. For further information on how eBay handles your personal data collected during the use of the eBay Careers website or job applications, please refer to the Talent Privacy Notice.,