Manager, Data Science 1

The Networker; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

eBay is seeking a Data Science Analyst for the View Item domain to apply advanced analytics, experimentation, and ML to inform product strategy and roadmap decisions. You will work with Product, Technology, and regional teams to translate insights into scalable improvements for buyers and sellers.

The role emphasizes strong technical depth, strategic thinking, and a passion for improving ecommerce at scale, with opportunities to shape measurement frameworks and guide long-term product direction.

Qualifications

• 7+ years of experience in analytics, data science, or a related quantitative field.
• Strong hands-on proficiency in SQL and Python or R.
• Experience applying statistical methods, experimentation, and machine learning techniques to real business problems.
• Familiarity with modern ML frameworks and approaches such as ensemble models, deep learning, or transformer-based methods; site experimentation is a plus.
• Demonstrated ability to connect insights to product growth opportunities and influence decisions.

Responsibilities

• Shape the View Item product roadmap by delivering insights and analytical leadership that influence product, engineering, and business decisions.
• Define and own success metrics, measurement frameworks, and experimentation roadmaps for View Item product areas.
• Apply advanced statistical methods and machine learning techniques to solve complex product and marketplace problems with buyer and revenue impact.
• Design, execute, and interpret A/B tests and other causal measurement approaches.
• Develop forward-looking analytical approaches, including predictive models to guide long-term strategy.
• Partner cross-functionally with senior stakeholders to translate findings into clear recommendations that improve buyer and seller outcomes at scale.

Skills

SQL

Python

R

Statistical modeling

A/B testing

Education

Bachelor's degree in Computer Science, Mathematics, Economics, Physics, or Engineering

Tools

ML frameworks

Job description

Job Summary

At eBay, were 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. Were 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 the team and the role:

Our team helps shape the future direction of eBay by defining where we play, how we win, and how we create differentiated experiences for our customers. We focus on deeply understanding the needs of core buyers and translating those insights into strategies that strengthen eBay s position in the market. To bring that strategy to life, we partner closely with Product, Technology, and regional business teams across the end-to-end customer experience.

Within this space, the View Item team plays a critical role in the buyer journey by helping customers evaluate products and make confident purchase decisions. As a Data Science Analyst supporting this domain, you will apply advanced analytics, experimentation, and machine learning to inform product strategy and influence roadmap decisions. This is a high-impact role for someone who combines strong technical depth with strategic thinking and brings a passion for improving the e-commerce experience at scale.

Responsibilities

• Shape the View Item product roadmap by delivering insights and analytical thought leadership that influence product, engineering, and business decisions.
• Define and own success metrics, measurement frameworks, and experimentation roadmaps for key View Item product areas, helping the team make faster and more confident decisions.
• Apply advanced statistical methods and machine learning techniques to solve complex, ambiguous product and marketplace problems with meaningful buyer and revenue impact.
• Design, execute, and interpret A/B tests and other causal measurement approaches to evaluate product changes and identify opportunities to improve the buyer experience.
• Develop forward-looking analytical approaches, including predictive and experimental models, to better understand customer behavior and guide long-term product strategy.
• Partner cross-functionally with senior stakeholders across Product, Engineering, and Business teams to translate complex findings into clear recommendations that improve buyer and seller outcomes at scale.

What you will bring

• 7+ years of experience in analytics, data science, or a related quantitative field, ideally supporting product decisions in an e-commerce or consumer technology environment.
• Strong hands-on proficiency in SQL and one or more analytical programming languages such as Python or R, with experience turning large-scale data into actionable insights.
• Experience applying statistical methods, experimentation, and machine learning techniques to real business problems, including descriptive and inferential analysis and predictive modeling.
• Familiarity with modern machine learning frameworks and approaches such as ensemble models, deep learning, or transformer-based methods; experience with site experimentation is a plus.
• Demonstrated ability to connect insights to product growth opportunities, think critically in ambiguous environments, and influence decisions through data-driven recommendations.
• Strong communication skills and a solid quantitative foundation, with a bachelor s degree or equivalent experience in a field such as Computer Science, Mathematics, Economics, Physics, or Engineering; advanced study is a plus.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.