Data Scientist, Knowledge Management

Job Summary

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 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.

This is a high-agency, startup-style role - if you thrive in fast-moving, product-focused environments and love working closely with AI/ML, Product, and Engineering teams, this is for you.

What You'll Do

• Analyze Optimize eCommerce Product Data - Run deep SQL Python analyses to find opportunities in taxonomy, ontology, and structured data for search and 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.

What We're Looking For

• 4+ years of experience in analytics or data science roles
• Strong data and analytics skills - proficiency in SQL and 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).
• Model evaluation know-how - ability to define metrics and evaluation frameworks for assessing ML-driven taxonomy and classification models.
• Startup DNA - high agency, thrive in fast-paced, iterative environments with deep cross-functional collaboration.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.