Senior Data Scientist (L23) – Payments Analytics

As a Senior Data Scientist in the Payments Analytics team at eBay, you will leverage your expertise in SQL, Python, and experimentation to drive data-informed decisions, optimize payment experiences, and improve conversion, reliability, and monetization. You will analyze complex datasets, design A/B tests, build data pipelines, and communicate actionable insights to product and business stakeholders, contributing to the evolution of eBay's global marketplace.

Must Have

• Analyze large, complex datasets related to payment flows, conversion funnels, declines, fraud signals, and customer experience.
• Design, analyze, and interpret A/B tests and experiments, including defining success metrics, evaluating results, and communicating insights.
• Build and maintain SQL-based data pipelines, dashboards, and analytical datasets.
• Use Python for data wrangling, exploratory analysis, statistical modeling, and automation of analytical workflows.
• Partner with Product and Business teams to translate ambiguous problems into structured analytical approaches.
• Generate clear, actionable insights and communicate findings effectively.
• 2–4 years of experience in data analytics, data science, or a related role.
• Strong proficiency in SQL.
• Strong working experience with Python for data analysis.
• Solid understanding of A/B testing and experimentation.
• Experience working with large datasets in a data warehouse environment.
• Strong analytical thinking and problem-solving skills.
• Ability to communicate insights clearly to both technical and non-technical audiences.

Good to Have

• Experience in payments, fintech, e-commerce, or platform analytics.
• Exposure to statistical modeling, causal inference, or predictive techniques.
• Experience building dashboards using tools such as Tableau, Looker, or similar.
• Familiarity with data modeling concepts and analytics engineering practices.
• Experience working in a fast-paced, product-driven environment with global stakeholders.

Perks & Benefits

• Work on high-impact, mission-critical systems that power eBay’s global marketplace.
• Partner with experienced product and engineering leaders across geographies.
• Opportunity to grow analytical depth while influencing product and business strategy.
• Be part of a team evolving from traditional analytics to data products and experimentation-driven decision-making.

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Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

Job Title: Senior Data Scientist (L23) – Payments Analytics

Team

Payments Analytics | eBay

Location

Bangalore, India (Hybrid)

Role Overview

eBay Payments is a critical platform that enables seamless, secure, and scalable financial transactions across our global marketplace. As a Senior Data Scientist (L23) in the Payments Analytics team, you will partner closely with product managers and business stakeholders to drive data-informed decisions, optimize payment experiences, and improve conversion, reliability, and monetization outcomes.

This role is ideal for a hands-on analyst/data scientist with strong foundations in SQL, Python, experimentation, and analytical problem-solving, who is ready to take ownership of complex analyses and influence product and business decisions.

Key Responsibilities

• Analyze large, complex datasets related to payment flows, conversion funnels, declines, fraud signals, and customer experience.
• Design, analyze, and interpret A/B tests and experiments, including defining success metrics, evaluating results, and communicating insights.
• Build and maintain SQL-based data pipelines, dashboards, and analytical datasets to support recurring and ad-hoc analysis.
• Use Python for data wrangling, exploratory analysis, statistical modeling, and automation of analytical workflows.
• Partner with Product and Business teams to translate ambiguous problems into structured analytical approaches.
• Generate clear, actionable insights and communicate findings effectively through written narratives, dashboards, and presentations.
• Contribute to improving analytics best practices, data quality, and experimentation rigor within the Payments analytics team.

Required Qualifications

• 2–4 years of experience in data analytics, data science, or a related role.
• Strong proficiency in SQL (ability to write complex queries, joins, window functions, and optimize performance).
• Strong working experience with Python for data analysis (e.g., pandas, numpy, scipy, matplotlib/seaborn).
• Solid understanding of A/B testing and experimentation, including hypothesis formulation, metric selection, statistical significance, and result interpretation.
• Experience working with large datasets in a data warehouse environment.
• Strong analytical thinking and problem-solving skills, with attention to detail.
• Ability to communicate insights clearly to both technical and non-technical audiences.

Preferred Qualifications

• Experience in payments, fintech, e-commerce, or platform analytics.
• Exposure to statistical modeling, causal inference, or predictive techniques.
• Experience building dashboards using tools such as Tableau, Looker, or similar.
• Familiarity with data modeling concepts and analytics engineering practices.
• Experience working in a fast-paced, product-driven environment with global stakeholders.

What We’re Looking For

• A hands-on, curious analyst who enjoys digging into data and uncovering insights.
• Someone comfortable operating with ambiguous problem statements and turning them into structured analysis.
• A strong collaborator who can balance analytical depth with business relevance.
• An individual eager to grow into more product-focused and impact-oriented analytics work.

Why Join eBay Payments

• Work on high-impact, mission-critical systems that power eBay’s global marketplace.
• Partner with experienced product and engineering leaders across geographies.
• Opportunity to grow analytical depth while influencing product and business strategy.
• Be part of a team evolving from traditional analytics to data products and experimentation-driven decision-making.

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