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:
The Shipping Analytics team drives eBay’s shipping strategy through data-driven insights, advanced analytics, and experimentation. This global team focuses on improving reliability, accuracy, affordability, and ease of shipping at eBay by applying AI and innovative analytical approaches.
In this role, you will operate as a hands-on analytics leader, combining deep technical expertise with first-time people leadership. You will lead a small team while remaining a strong individual contributor, partnering closely with Product, Business, Finance, and Engineering teams. Your work will shape managed shipping solutions, carrier routing, delivery performance, and seller adoption of eBay labels, with direct impact on cost, reliability, and profitability across eBay’s global shipping ecosystem.
What you will accomplish:
Apply advanced analytics and AI to solve complex shipping and logistics problems across domestic and cross-border experiences
Define success metrics and drive analytics to launch, expand, and scale eBay’s managed shipping and label platforms globally
Build predictive models and simulations to optimize carrier selection, cost, speed, reliability, and sustainability
Identify seller and customer friction points and recommend data-informed product and business solutions to increase label adoption
Design, run, and evaluate experiments (A/B tests) to guide decisions on product features, pricing, and policy
Develop data pipelines, dashboards, and AI-powered anomaly detection systems to enable real-time performance monitoring
Partner with cross-functional teams to translate insights into measurable business outcomes and operational improvements
What you will bring:
A Bachelor’s degree in a quantitative field such as Engineering, Computer Science, Economics, Statistics, or Mathematics; a Master’s degree or MBA is a plus
8+ years of experience in data science, analytics, or a related quantitative role
First experience leading people, while remaining hands-on as a strong individual contributor
Proven ability to independently own high-impact analytical initiatives end to end
Strong expertise in SQL, Excel, and data visualization tools; proficiency in Python or R preferred
Experience with product analytics, experimentation (A/B testing), and causal inference
Clear communication skills and the ability to translate complex analyses into actionable recommendations for diverse partners
Experience with global logistics or shipping data is a big plus
#LI-CH2
Please see the for information regarding how eBay handles your personal data collected when you use the eBay Careers website or apply for a job with eBay.
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. If you have a need that requires accommodation, please contact us at . We will make every effort to respond to your request for accommodation as soon as possible. View our to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.
The eBay Jobs website uses cookies to enhance your experience. By continuing to browse the site, you agree to our use of cookies. Visit our for more information.
:quality(80))
:quality(80))
:quality(80))