Data Scientist

eBay; Bengaluru; On-site; INR 800,000 - 1,400,000; Full time

Job summary

eBay is seeking an early-career data analytics professional to join our Product Knowledge organization in Bengaluru. You will write SQL queries, build Python scripts, and experiment with LLM prompts to improve taxonomy, ontology, and catalog data for search and recommendations.

You will work closely with data scientists, product managers, and engineers to test data hypotheses, evaluate model performance, and accelerate AI-driven data enrichment in a fast-paced, startup-like environment.

Qualifications

• 2 to 7 years of hands-on experience in data analytics, product analytics, or data science roles.
• Solid proficiency in SQL and Python for data extraction, manipulation, and analysis.
• Strong interest in eCommerce search, recommendations, or knowledge graphs.
• Hands-on familiarity with LLMs, prompt engineering, or RAG concepts.

Responsibilities

• Analyse eCommerce product data by running SQL queries and Python scripts to analyze taxonomy, ontology, and catalog data.
• Experiment with prompt engineering workflows to automate data enrichment and taxonomy validation.
• Support model evaluation by testing product knowledge models and semantic search solutions against defined metrics.
• Collaborate with data scientists, product managers, and engineers to execute data strategies and refine AI-based classification models.
• Build quick prototypes to test data hypotheses and validate new structured data ideas for better product discovery.

Skills

SQL

Python

Data analytics

AI/ML curiosity

Prompt engineering

Tools

LLMs

Job description

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.

What You’ll Do

• Analyse 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.

What We’re Looking For

• Experience: 2 to 7 years of hands-on experience in a data analytics, product analytics, 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.

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.