Data Scientist 1, Knowledge Management

eBay
San Jose, United States of America
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Remote
San Jose, United States of America

Tech stack

Artificial Intelligence
Graph Database
Knowledge Management
SQL Databases
Test Data
Usage Analysis
Scripting (Bash/Python/Go/Ruby)
Large Language Models
Prompt Engineering
Model Validation
Data Strategy
Data Analytics

Job 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.

Requirements

  • 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.

Benefits & conditions

Why Join Us?

  • Kickstart Your AI Career: Get hands-on, real-world experience with AI/ML and LLMs in a high-scale environment.
  • Learn from the Best: Work directly alongside senior AI, Data Science, and Product teams.
  • Fast-Track Growth: Build foundational skills rapidly in a supportive, high-velocity, startup-like culture.
  • Make a Visible Impact: See your data analysis directly improve how millions of users discover products.

About the company

At eBay, we're more than a global ecommerce leader - we're changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We're committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts. Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work - every day. We're in this together, sustaining the future of our customers, our company, and our planet. Join a team of passionate thinkers, innovators, and dreamers - and help us connect people and build communities to create economic opportunity for all. About Team And Role We're building the future of eCommerce product discovery, and we need a data-driven, AI-curious problem solver to join our team. This is an exciting, hands-on role at the intersection of data analytics, AI/ML experimentation, and prompt engineering-ideal for an early-career professional who loves writing SQL queries, building Python scripts, and experimenting with LLMs to solve real-world problems. You'll be embedded in the Product Knowledge org, helping us clean, structure, and optimize taxonomy, ontology, and catalog data for next-gen search and recommendation engines. If you are eager to learn, thrive in fast-moving environments, and want to work directly with AI/ML, Product, and Engineering teams, this is the perfect place to accelerate your career.

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