SEO Data Scientist

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. About the team and the role: Our team helps build the future strategic direction of eBay by defining where we play, how we win, and how we develop 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 work in close coordination with Product, Technology, and regional business teams across the end-to-end customer experience. Within this space, we are seeking a Data Scientist for the SEO Analytics function at eBay. In this role, you will partner closely with the product and engineering teams, using eBay’s vast data ecosystem to uncover insights, influence the SEO roadmap, and drive customer-centric innovation across our marketplace. What you will accomplish: Develop the SEO product roadmap by delivering insights and analytical thought leadership that influence design, technical, and organizational decisions. Define and own success metrics, measurement frameworks, and experimentation roadmaps for key product areas, helping the team make faster and more confident decisions. Understand and improve SEO/AEO performance in a constantly evolving environment. Identify root causes behind performance changes, including product launches, technical issues, algorithm updates, AI search trends, and external market factors. Apply sophisticated statistical methods combined with predictive analytics to address complex, ambiguous product and marketplace problems with significant buyer and revenue impact. Design and interpret A/B tests and other causal measurement approaches to evaluate product changes and find 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 Product, Engineering, and Business teams to translate complex findings into clear recommendations that improve buyer and seller outcomes at scale.

8+ 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 command of A/B testing design, causal inference, and experimentation measurement. 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 approaches for solving 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. Proven 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 proven 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