Data Science - Manager
eBay (company site, opens in a new tab)7–10 yrsBengaluruOn-siteDirect career pageEst. 35–55 LPA
Posted 7h ago
Reach people at eBay
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at eBay you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Analyze buyer and seller behavior and marketplace trends to identify opportunities for category growth and improved engagement, conversion, retention, and GMV.
- Lead and manage the full experimentation lifecycle including hypothesis formation, A/B test design, result analysis, and impact measurement to inform business decisions.
- Design and implement Agentic AI solutions to automate analytics workflows and make insights accessible across teams, while developing measurement frameworks and dashboards to track performance.
Minimum Requirements
- 7–10 years of experience in data science, product analytics, business analytics, or a related field.
- Proficiency in SQL and Python for analyzing large datasets and addressing business questions.
- Experience managing end-to-end experimentation, including A/B testing and statistical analysis.
- Hands-on experience implementing Agentic AI solutions such as AI agents or LLM-based workflows for analytics or business decision-making.
Ideal Candidate Profile
- Experienced in e-commerce, online marketplaces, retail, or consumer technology environments with understanding of marketplace dynamics such as customer engagement and seller performance.
- Demonstrated ability to lead cross-functional collaboration with Product, Engineering, Marketing, and Category Management teams to align analytics with business priorities.
- Proficient in applying advanced experimentation methods, causal inference, and measurement frameworks to evaluate business initiatives and product changes.