Data Science - Analyst 3

About 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.

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.

Requirements

• 3–5 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.

Qualifications

• Experience working in a fast-paced, dynamic environment with a focus on innovation and continuous improvement.
• Ability to work independently and collaboratively with cross-functional teams.
• Strong problem-solving and analytical skills.
• Excellent written and verbal communication skills.

Skills

• Advanced proficiency in SQL and one or more analytical programming languages such as Python or R.
• Experience with statistical methods, experimentation, and machine learning techniques.
• Knowledge of modern machine learning frameworks and approaches.
• Experience with A/B testing and causal measurement approaches.
• Ability to develop predictive and experimental models.
• Strong collaboration and partnership skills.

Benefits

• Competitive base pay range: $127,600 - $170,300.
• Target bonus and restricted stock units (if applicable).
• Full range of medical, financial, and/or other benefits, including 401(k) eligibility and various paid time off benefits.

Pay

The base pay offered may vary depending on multiple individualized factors, including location, skills, and experience.

Schedule

This role is remote-friendly and eligible for U.S. visa sponsorship.

Company

Ebay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status.