Fast-paced, dynamic, and proactive, eBay's Trust & Risk team is dedicated to making eBay a safe and trusted platform for the millions of buyers and sellers who make up the eBay community.

Key Trust & Risk initiatives at eBay span platform communications, seller protections and policy experiences, buyer and seller feedback, the eBay Money Back Guarantee, seller performance, new seller onboarding, and transaction risk management. The team is committed to maintaining and enhancing eBay as a safe and reliable marketplace while strengthening how we measure, understand, and reduce transaction-related losses. We continuously improve the customer experience while ensuring eBay remains a secure and trusted global marketplace.

As a Data Scientist in the Trust & Risk team at eBay, you will work with Trust and Risk business teams and partner teams across Product, Engineering, Policy, Shipping, and Design to analyze marketplace problems, identify opportunities, and support data-driven decision-making. Your role will involve using analytics and quantitative methods to understand customer and transaction risk trends, measure business impact, and evaluate opportunities to improve customer experience and reduce losses. You will also contribute to the development of metrics, analytical frameworks, and scalable insights across the Trust & Risk organization.

Responsibilities :

- Generate Analytical Insights: Apply analytical and quantitative methods to understand Trust & Risk business problems and provide insights that support business and operational decisions.

- Analyze & Identify Opportunities: Conduct analyses of marketplace and transaction risk issues to identify opportunities to improve customer experience, strengthen trust, and reduce losses for buyers, sellers, and eBay.

- Define & Monitor Metrics: Develop and monitor Key Performance Indicators (KPIs) and supporting metrics related to customer trust, transaction risk, loss, decision quality, and customer experience. Investigate underlying drivers of metric movements and surface actionable insights.

- Deliver Results: Support business objectives by executing analytical projects, measuring outcomes, and translating findings into recommendations that improve customer experience and business performance.

- Cross-Functional Collaboration: Work closely with partners across Trust, Risk, Product Management, Engineering, Policy, Shipping, and Design to understand business questions and incorporate analytical insights into decision-making.

To be successful in this role :

- Educational Background & Experience: BA/BS degree with 1-3 years of relevant experience, or an advanced degree with relevant experience, across areas such as Quantitative Research, Analytics, or Data Science.

- Data Analysis Expertise: Ability to analyze large and complex datasets, recognize trends and patterns, and translate findings into meaningful business insights.

- Technical Skills: Proficiency in programming (Python/R) and data querying (SQL).

- Problem-Solving: Strong analytical thinking and creativity in solving structured and moderately ambiguous problems.

- Execution & Results: Ability to independently execute well-scoped analytical projects and deliver high-quality results.

- Customer & Business Orientation: Ability to understand customer and business needs and use data to evaluate trade-offs across customer experience, risk, and business outcomes.

- Communication: Ability to clearly communicate analytical findings and recommendations to technical and non-technical stakeholders.

- Availability: Flexible and capable of working remotely across multiple time zones. Regular availability is required for meetings between 9:00 AM and 12:00 PM (PDT).

Additionally, the following background and experience is helpful :

- Prior experience in marketplace Trust, Risk, fraud, or transaction risk analytics.

- Experience working with customer, transaction, risk, or loss-related datasets.

- Ability to present complex analyses and insights effectively in simple terms.

- Experience in a technology company.

- Background in e-commerce products, marketplaces, payments, or shipping.

- Experience with Natural Language Processing or LLM/GenAI is a plus.