Data Science - Manager

Job Summary

At eBay, we're 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. We're 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.

Role Overview

Data Scientist (Analytics) - Focus Category Analytics

We are looking for a Data Scientist (Analytics) to join our Focus Category Analytics team. Our team uses data to understand marketplace trends, improve customer experiences, and support growth across key eBay categories, including Collectibles, Luxury, Sneakers, Apparel, Parts and Accessories and Vehicles.

In this role, you will help teams make informed decisions by analyzing customer behavior, measuring business performance, and evaluating new ideas through experimentation. You will work with partners across Product, Engineering, Marketing, and Category Management to identify opportunities and recommend improvements.

You will also explore and implement Agentic AI solutions that make analytics more efficient and help teams access insights faster.

This role offers opportunities to take ownership of meaningful analytical projects, work with a variety of business partners, and see how your recommendations influence customer experiences and business outcomes.

What You Will Accomplish

• Support category growth: Analyze buyer and seller behavior, marketplace trends, and category performance to identify opportunities to improve engagement, conversion, retention, and GMV.
• Lead experimentation: Manage the full experiment lifecycle, from defining hypotheses and designing A/B tests to analyzing results, measuring impact, and recommending next steps.
• Turn data into decisions: Use SQL, Python, and statistical methods to investigate business questions, explain findings, and recommend actions that improve marketplace performance.
• Apply Agentic AI: Design and implement AI agent solutions that simplify analytical workflows, automate recurring tasks, and make insights more accessible to business teams.
• Develop measurement frameworks: Work with partners to define success metrics, track performance, and build dashboards that support ongoing decisions.
• Understand customer experiences: Use funnel analysis, customer segmentation, and behavioral insights to identify areas where buyers and sellers may benefit from improvements.
• Measure business impact: Apply experimental and causal measurement methods to understand the outcomes of product changes and business initiatives.
• Collaborate across teams: Partner with Product, Engineering, Marketing, and Category Management to align analytical work with business priorities.
• Share recommendations: Present findings in a clear, practical way so teams can understand results, evaluate options, and take action.

What You Bring

• 7-10 years of experience in data science, product analytics, business analytics, or a related field.
• Experience using SQL and Python to analyze large datasets, identify trends, and answer business questions.
• Experience managing end-to-end experimentation, including hypothesis development, experiment design, A/B testing, statistical analysis, result interpretation, and recommendations.
• Knowledge of statistics, hypothesis testing, experimental design, and causal inference, with the ability to select appropriate methods for different business questions.
• Hands-on experience implementing Agentic AI solutions, including AI agents or LLM-based workflows, to support analytics, automation, or business decision-making.
• Experience using analytical methods such as funnel analysis, cohort analysis, segmentation, and performance measurement.
• Ability to translate complex data into clear findings and practical recommendations.
• Experience collaborating with cross-functional teams to understand business needs, solve problems, and support decisions.
• Communication skills that help technical and non-technical audiences understand analytical findings and their implications.

What Will Help You Succeed

• Experience working in e-commerce, online marketplaces, retail, or consumer technology.
• Understanding of marketplace dynamics, including customer engagement, seller performance, pricing, and product selection.
• Familiarity with advanced experimentation methods and measuring the impact of business initiatives.
• Experience with Generative AI, LLM applications, AI agent frameworks, or workflow automation tools.
• Exposure to machine learning, personalization, recommendation systems, or predictive analytics.
• Interest in learning new analytical approaches and using technology to improve how teams work.

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.