> Markdown version of [/jobs/ext/1345510-data-scientist-1-knowledge-management](https://www.wearedevelopers.com/jobs/ext/1345510-data-scientist-1-knowledge-management). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist 1, Knowledge Management - **Company:** eBay - **Location:** San Jose, CA, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Graph Database, Knowledge Management, SQL Databases, Test Data, Usage Analysis, Scripting, Large Language Models, Prompt Engineering, Model Validation, Data Strategy, Data Analytics - **Published:** July 19, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p5tw10thui ## About the Role * Experience: 2+ years of hands-on experience in a data analytics, product analytics, or junior data science role. * Core Technical Skills: Solid proficiency in SQL and Python for data extraction, manipulation, and analysis. * Eagerness to Learn: Strong interest in eCommerce search, recommendations, or knowledge graphs (prior exposure is a big plus). * AI/LLM Curiosity: Hands-on familiarity or side-project experience with LLMs, prompt engineering, or RAG concepts. * Analytical Mindset: Ability to look at data, spot patterns, and clearly communicate findings to immediate team members. * Growth Mindset: High energy, adaptability, and the ability to thrive and pick up new skills quickly in a fast-paced environment. ## Description * Analyze eCommerce Product Data: Run SQL queries and Python scripts to analyze taxonomy, ontology, and catalog data, identifying gaps and opportunities for search improvement. * Experiment with LLMs: Assist in building and testing prompt engineering workflows to automate data enrichment, product classification, and taxonomy validation. * Support Model Evaluation: Help test and evaluate the performance of product knowledge models, semantic search solutions, and embeddings against defined metrics. * Collaborate Cross-Functionally: Work closely with data scientists, product managers, and engineers to execute data strategies and refine AI-based classification models. * Build Quick Prototypes: Move fast to test data hypotheses, run experiments, and help validate new structured data ideas for better product discovery. ## Related Videos - [Dirty Tests And How To Clean Them](https://www.wearedevelopers.com/videos/515-dirty-tests-and-how-to-clean-them) - [JavaScript? No. Java Scripts! - Scripting with Java](https://www.wearedevelopers.com/videos/2094-javascript-no-java-scripts-scripting-with-java) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Stop Guessing, Start Measuring: Evaluating RAG Systems with Synthetic Test Data](https://www.wearedevelopers.com/videos/1982-stop-guessing-start-measuring-evaluating-rag-systems-with-synthetic-test-data) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)