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.
What you will accomplish:- 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:- 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.
Additional DetailsThe base pay range for this position is expected in the range below:
$127,600 - $170,300
Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
If hired, employees will be in an "at-will position" and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
Remote roles are not eligible for U.S. visa sponsorship.
