Data Scientist Knowledge Management jobs at Ebay in India, Bengaluru

We’re seeking a Member of Technical Staff 1 (Software Engineer) who can work independently and is an expert in distributed systems . You’ll design and deliver well-scoped services and features that advance eBay’s Core Data Platform—improving scalability, reliability, and developer experience. This role is Data Platform Engineering not data engineering ): you’ll build and evolve the platform itself rather than author application pipelines.

• Independently design, implement, and ship distributed services and features end-to-end (design → code → tests → deploy → operate).

• Build core platform capabilities across ingestion, streaming, lakehouse/warehouse, catalog, and governance .

• Write production-grade code with strong observability (metrics, logs, traces) and SLOs , and participate in on-call for the services you own.

• Diagnose and resolve performance, scalability, and correctness issues in distributed environments.

• Contribute design docs for your areas; participate in reviews to uphold reliability, security, and cost best practices.

• Collaborate with product, infra, and analytics teams to align technical work with business outcomes.
  

• 6+ years of professional software engineering experience (or equivalent impact).

• Expertise in distributed systems fundamentals (consensus, replication, partitioning, consistency models, fault tolerance) and practical experience building and running such systems in production.

• Strong coding skills in Java/Python and familiarity with CI/CD .

• Hands-on with some of: Kafka/Flink , Spark , Delta/Iceberg , Kubernetes , NoSQL/columnar stores .

• Proven ability to work independently , make sound tradeoffs, and deliver quality outcomes with minimal supervision.

• Solid debugging, performance analysis, and system design skills.
  

• multi-tenant platform services, data governance, or privacy-by-design controls.

• Contributions to open-source distributed systems or data platforms.
  

• ships independent, well-scoped features/services to production with strong reliability.

• Demonstrably improves throughput/latency/cost or availability/SLOs on owned services.

• Becomes a go-to engineer for distributed-systems debugging and design conversations within the team.

• Maintains high code quality, test coverage, and quality-in-release metrics.
  

• Impact at scale: Your platform work powers analytics and ML across a global marketplace.

• Hard problems: Streaming freshness/correctness, storage/compute efficiency, multi-region resiliency.

• Collaborative culture: Inclusive team that values autonomy, craftsmanship, and knowledge sharing.

• Growth:

We’re on a mission to build the most intelligent and scalable product knowledge system in eCommerce, powered by AI, structured data, and next-gen taxonomy/ontology strategies.

In this high-agency, startup-like role, you’ll own and scale the AI-driven product knowledge ecosystem, ensuring our taxonomy, ontology, and catalog data power better search, recommendations, and personalization experiences.

What You’ll Do

• Define & Implement Product Knowledge Strategy – Own the roadmap for taxonomy, ontology, structured data, and knowledge graph initiatives, aligning with AI/ML and Product teams.

• Drive AI-Powered Taxonomy & Ontology Development – Partner with data scientists, engineers, and analysts to build, test, and scale ML-driven classification, entity resolution, and knowledge graph models.

• Improve Search & Product Discovery – Ensure our structured product data directly enhances search relevance, filtering, and recommendation algorithms.

• Develop & Enforce Data Standards – Lead governance for taxonomy updates, structured metadata, and attribute standardization, ensuring a scalable and accurate catalog.

• Enable LLMs for Product Knowledge – Work with AI teams to develop LLM-powered solutions for automated tagging, classification, and enrichment.

• Measure & Iterate – Define key metrics and evaluation frameworks to track the impact of structured data improvements on search, recommendations, and personalization.

• Deeply Integrate with AI/ML Teams – Work hand-in-hand with AI, data science, and engineering to build scalable, automated solutions for product classification and catalog intelligence.

• Product Leadership in Data/AI – 10+ years in product management, ideally in eCommerce, search, recommendations, or AI-driven product knowledge systems.

• AI & Data Fluency – Experience working with ML models, knowledge graphs, LLMs, and structured data strategies to drive business outcomes.

• Taxonomy & Ontology Expertise – Strong understanding of product classification, metadata structuring, and entity resolution techniques.

• Search & Discovery Focus – Experience optimizing product search, recommendations, and structured navigation.

• Technical Comfort – Familiarity with SQL, APIs, data pipelines, and AI/ML workflows.

• High-Agency & Execution-Driven – Startup-like attitude with the ability to drive cross-functional alignment, influence without authority, and deliver results fast.

• Strong Analytical & Communication Skills – Ability to translate data-driven insights into clear product strategies.

• Shape the AI-powered future of eCommerce product discovery.

• Be at the forefront of AI-driven taxonomy, ontology, and knowledge graph development.

• Work in a high-agency, startup-like culture where your decisions directly impact millions of users.

• Collaborate with ground breaking AI/ML teams to redefine structured data for eCommerce.

• Drive innovations that enhance search, personalization, sellingg and product discovery.

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 just as 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.

● Analyze & Optimize eCommerce Product Data – Run deep SQL & Python analyses to identify opportunities in taxonomy, ontology, and structured data for search & 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.

● Strong Data & Analytics Skills – Proficiency in SQL & 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 )

At the intersection of AI, data science, and product discovery , we’re crafting the next generation of eCommerce experiences—and we’re looking for a dynamic leader to help make that vision real.

As , you’ll be a key architect behind the structured data that fuels search, recommendations, and AI-driven personalization. You’ll lead with both hands-on expertise and strategic insight, bridging the worlds of LLMs, taxonomy, knowledge graphs, and scalable analytics .

This is a embedded in our , where you’ll drive meaningful innovation across catalog systems, metadata, and data-driven product experiences. If you thrive in a fast-paced, startup-like environment and are passionate about turning complex data into magical customer experiences, this is your stage.

What You’ll Lead & Deliver

• Optimize Product Knowledge at Scale
  Conduct deep analytical dives using SQL and Python to enhance taxonomy, ontology, and structured catalog data that directly impact product discovery.

• Build LLM-Powered Solutions
  Use prompt engineering and retrieval-augmented generation (RAG) to create scalable, AI-powered tools for classification, data enrichment, and catalog intelligence.

• Design Model Evaluation Frameworks
  Establish robust metrics and test beds to evaluate semantic search models, embeddings, and ML-powered classification systems.

• Turn Data into Strategy
  Translate insights into action by partnering with Product, Engineering, and AI teams—driving roadmap priorities for catalog optimization, entity resolution, and knowledge graph evolution.

• Prototype & Experiment Rapidly
  Move quickly to test ideas and validate structured data strategies. Build proof-of-concepts that can scale into enterprise-level solutions.

• Partner for Production Impact
  Collaborate closely with applied ML, engineering, and product teams to refine and operationalize AI models in real-world, high-scale systems.

What You Bring

• 7+ years of experience in analytics, data science, or ML roles

• Advanced proficiency in SQL and Python for analytics, automation, and experimentation

• Familiarity with eCommerce discovery , product classification, and search or recommendation systems

• Hands-on experience with LLMs, prompt engineering, or RAG (preferred but not required)

• Strong grasp of model evaluation , including metrics design and benchmarking

• A startup mindset—bias for action, high ownership, and comfort with ambiguity

• Excellent communicator with the ability to influence cross-functional stakeholders

Why You’ll Love It Here

• Drive real impact at the core of product discovery innovation

• Work hands-on with cutting-edge AI and data platforms

• Collaborate with some of the best minds in AI, Product, and Engineering

• Own high-visibility projects in a startup-like, high-trust culture

• Build scalable, magical, and relevant product data systems used by millions

About the Role

The ideal candidate will apply advanced analytics and data science techniques to:

• Drive innovation,
• Build scalable data products, and
• Deliver actionable recommendations through rigorous analysis.

Key Responsibilities

• Apply strong analytical and statistical skills to solve complex and unstructured business problems with structured, data-supported solutions.
• Drive product decisions using A/B testing techniques and experimental design.
• Lead innovation and continuous improvement within the Focus Category Analytics team.
• Develop data products that enable faster and more accurate decision-making.
• Leverage advanced analytics tools and data science models to solve category-level challenges.
• Collaborate with cross-functional teams — including Business, Product Management, Engineering, and Finance — to identify, prioritize, and resolve key business challenges.
• Serve as a trusted partner and advisor to senior leaders, translating complex analytical insights into actionable business recommendations.
• Create tools, dashboards, and reports to monitor and ensure program success.

Additional Requirements

• This role operates in a hybrid work model .
• Flexibility to attend late evening meetings (audio/video conferences) with U.S. or Europe-based teams, and to occasionally respond to emails or complete tasks during late evenings.

What We Expect From You

• Bachelor’s degree in Engineering, Computer Science, Economics, Statistics, Mathematics , or a related quantitative field.
  • Master’s degree or MBA preferred.
• 6+ years of experience in data science, analytics, or a related field .
• Strong analytical skills with proficiency in:
  • SQL
  • Excel
  • Data visualization tools (e.g., Tableau, Power BI, Looker)
• Proficiency in statistical programming languages such as Python or R .
• Background in product analytics , with hands-on experience in A/B test design and measurement preferred.
• Proven track record of using analytics and data science to:
  • Drive significant business impact,
  • Build predictive models, and
  • Solve optimization or elasticity problems.
• Excellent communication skills with the ability to translate technical findings into business insights for non-technical audiences.
• Experience working in a fast-paced, cross-functional environment .

What you will accomplish:

• Modeling & NLP Development
  • Design LLM-based pipelines (e.g., using Langchain frameworks) to identify and summarize customer pain points from textual data.
  • Develop summarization, clustering, and topic modeling approaches to group recurring themes across markets and product lines.
  • Apply prompt engineering , retrieval-augmented generation (RAG) , and embedding search to improve model accuracy and relevance.
  • Use machine learning methods in concert with LLM.

• Data Engineering & Processing
  • Build and maintain data pipelines to ingest and clean data from diverse sources (e.g., surveys, customer support tickets, product reviews, social media, and CRM systems).
  • Ensure data quality, scalability, and compliance with internal governance and data privacy policies.
  • Productionize models and integrate outputs with downstream systems and dashboards.

• Insights Delivery & Visualization
  • Design and build interactive visualizations (in JavaScript) that make model outputs accessible and actionable for non-technical stakeholders.
  • Partner with Insights teams to create data stories and presentations that influence business strategy using clear, human-readable summaries of complex findings.

What you will bring:

• Ability to derive insight from data, visualize it appropriately and influence others to drive outcomes
• MSc or PhD in Computer Science, Data Science, Statistics, or a related field .
• 4+ years of experience in machine learning , NLP , or data-driven product development .
• Strong coding proficiency in Python (Pandas, PyTorch, Hugging Face, LangChain, umap, hdbscan, etc.)
• Strong experience with front end development with JavaScript and data visualization libraries (e.g. D3.js)
• Experience deploying and managing machine learning services in containerized environments using Docker and Kubernetes .
• Deep understanding of vector databases , semantic search , and embedding-based retrieval systems .
• Proficient with GitHub and modern version control best practices (e.g. code reviews, CI/CD workflows).
• Proven experience working with large-scale unstructured text data .

Shape the Future of AI-Driven eCommerce Discovery

You’ll join the org and play a key role in designing the backbone of next-gen search, recommendations, and generative AI experiences.

What You’ll Work On

• Transform Product Data into Insights
  Conduct deep-dive SQL and Python analyses to uncover opportunities in taxonomy, ontology, and catalog structure that enhance discovery and user experience.

• Harness the Power of Generative AI
  Use prompt engineering and LLMs to create innovative tools for classification, taxonomy validation, and data enrichment.

• Build & Evaluate AI/ML Models
  Design frameworks to evaluate product knowledge models, semantic embeddings, and ML-based categorization systems.

• Drive Data-Informed Strategy
  Translate complex findings into clear, actionable insights for Product and Engineering teams. Influence roadmap decisions on entity resolution, catalog optimization, and knowledge graph development.

• Partner Across Functions
  Collaborate closely with Applied Research, Engineering, and Product teams to build and deploy high-impact data and AI solutions at scale.

• Experiment & Innovate Fast
  Prototype quickly, validate hypotheses, and iterate on structured data and AI-driven solutions that push boundaries.

What You Bring

• 12+ years of experience in data science or analytics roles, including 5+ years leading teams

• Proven track record building data products, knowledge graphs, and scalable data pipelines

• Deep understanding of eCommerce search, recommendation systems, and product analytics

• Hands-on experience with LLMs, prompt engineering, and RAG techniques (preferred)

• Strong communication skills and ability to influence cross-functional stakeholders

• Experience evaluating ML models with custom metrics and robust frameworks

• Startup mindset—comfortable with ambiguity, bias for action, and fast iteration

Why Join Us

• Be at the forefront of AI-powered product discovery in eCommerce

• Own high-impact initiatives in a startup-style culture with real autonomy

• Work alongside world-class talent across AI, Product, and Engineering

• Build solutions that scale—serving millions of users and shaping the future of shopping

Ready to lead the next wave of AI + Data innovation in commerce? Let’s build the future together.