Ebay Senior Manager Knowledge Science 

India, Karnataka, Bengaluru 

122515206

We’re building the future of eCommerce product discovery, and we need a data-driven, AI-savvy problem solver to help us do it.

This is a unique role at the intersection of data analytics, AI/ML model evaluation, and prompt engineering—ideal for someone who is just as comfortable writing SQL queries and Python scripts as they are experimenting with LLMs to build analytical solutions.

You’ll be embedded in the Product Knowledge org, shaping how we structure and optimize taxonomy, ontology, and catalog data for next-gen search, recommendations, and AI-driven experiences.

● Analyze & Optimize eCommerce Product Data – Run deep SQL & Python analyses to identify opportunities in taxonomy, ontology, and structured data for search & discovery improvements.

● Leverage LLMs for Analytical Solutions – Use prompt engineering techniques to create AI-driven approaches for taxonomy validation, data enrichment, and classification.

● Evaluate & Improve AI/ML Models – Develop systematic evaluation frameworks for product knowledge models, embeddings, and semantic search solutions.

● Drive Insights & Strategy – Use data-driven storytelling to influence product and AI teams, helping shape decisions on catalog optimization, entity resolution, and knowledge graph development.

● Integrate with AI/ML Teams – Work closely with data scientists and engineers to test and refine AI-based classification, search ranking, and recommendation models.

● Prototype and Experiment – Move fast, test hypotheses, and build quick experiments to validate structured data strategies and AI-driven discovery improvements.

● Strong Data & Analytics Skills – Proficiency in SQL & Python for data wrangling, analytics, and automation.

● Product Analytics Mindset – Familiarity with eCommerce search, recommendations, and knowledge graph applications

● Strong Communication – Ability to turn complex findings into actionable recommendations for Product, AI, and Engineering teams.

● AI/LLM Experience – Hands-on experience with LLMs, prompt engineering, and retrieval-augmented generation (RAG) for AI-powered insights (Preferred )