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Tier-1 brand, Bangalore location, mid-level ML role, and broad skillset increase applicant competition.
ML/AI engineering skills are transferable, yet e-commerce product discovery domain knowledge adds moderate specificity.
Explicit 3–6 years and mandatory ML, SQL, Python, deployment, and visualization skills make screening strict.
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Lead development and scaling of eBay's internal AI analytics platform encompassing NL-to-SQL pipelines, domain knowledge bases, and automated dashboards.
Develop, deploy, and maintain predictive models and AI-powered decisioning tools to improve product discovery, targeting, and measurement in Focus Category domains.
Collaborate cross-functionally to deliver actionable data insights and build interactive dashboards for non-technical users, influencing strategic business decisions.
3–6 years of relevant professional experience in data science, machine learning, or analytics.
Strong proficiency in SQL (SparkSQL/Hive preferred), Python, and working knowledge of JavaScript for building interactive dashboards.
Bachelor's or advanced degree in Statistics, Applied Econometrics, Mathematics, Physics, Computer Science, or related field.
Experience in building and deploying machine learning models and implementing data visualization with tools like Tableau, ECharts, or Plotly.
Experienced in operationalizing ML models from prototype to production, including cloud-based ML platform use and AI deployment pipelines.
Skilled in advanced AI/ML, especially with large language models (LLMs) and prompt engineering for production AI systems.
Capable of bridging data warehouse architectures and AI analytics products, with experience in NL-to-SQL systems and knowledge base design in complex data environments.