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Tier-1 brand, metro location, popular ML/Data title, and mid-level experience amplify competition.
ML and LLM skills transfer across industries, but eCommerce taxonomy domain adds moderate specialization.
Explicit 4+ years plus mandatory SQL/Python and ML model evaluation increases filter rigidity.
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Analyze and optimize eCommerce product taxonomy, ontology, and catalog data using deep SQL and Python analyses to improve search and discovery.
Leverage large language models (LLMs) and prompt engineering to create AI-driven taxonomy validation, data enrichment, and classification solutions.
Develop and implement evaluation frameworks for AI/ML models related to product knowledge, embeddings, and semantic search; collaborate with AI/ML teams to refine models and drive data-informed product decisions.
Minimum 4 years of experience in analytics or data science roles.
Proficiency in SQL and Python for data wrangling, analytics, and automation.
Experience with eCommerce product search, recommendations, or knowledge graph applications.
AI/LLM and model evaluation experience is preferred but not explicitly mandatory.
Experienced in product analytics with a strong bias towards eCommerce search and discovery systems.
Comfortable working in fast-paced, startup-like environments with high agency and iterative cross-functional collaboration.
Skilled at translating complex analytical insights into actionable recommendations for Product, AI, and Engineering teams.