Product Manager - Paid Search / Acquisition at StubHub in New York, NY

Job description

StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we’re here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world. StubHub is seeking a Product Manager, Paid Search / Acquisition to build and improve the systems that support acquisition across StubHub and viagogo. You will own the product roadmap, set backlog priorities, and coordinate delivery across Engineering, Data Science, Analytics, and Operations. Your work will help these systems make better decisions and improve business results at scale. This role focuses on automated decision systems and internal platforms. You will turn complex business and technical problems into clear product requirements and delivery plans. You will need to understand data flows, system dependencies, and technical trade-offs, and connect product decisions to revenue, profit, and operating efficiency. Location: Hybrid (3 days in office / 2 days remote) – New York, NY About the Team: The Acquisition team helps fans discover live events across StubHub and viagogo. Paid Search brings together Product, Data Science, Analytical Engineering, Software Engineering, and Operations. We build the software, data, measurement, and workflows that support paid search across Google and Microsoft Advertising. Our work includes automated bidding, campaign management, experimentation, and attribution. We improve these capabilities through product development and measure their effect on business results. What You'll Do: Own the product roadmap and backlog. Set priorities based on expected business impact, technical risk, effort, and team capacity. Coordinate delivery across Engineering, Data Science, Analytics, and Operations. Agree on owners and milestones, manage dependencies, resolve blockers, and keep teams informed. Develop the systems that automate bidding, campaign structure, keyword coverage, and ad assets. Use recurring operational problems to identify product improvements that work at scale. Define product requirements, acceptance criteria, and release checks with technical partners. Assess data flows, system interfaces, and failure cases when choosing an approach. Partner on attribution, data quality, measurement, and policy constraints. Trace how these affect system decisions and agree on how to validate a solution. Translate commercial goals into product priorities. Explain the expected benefit, cost, risks, and trade-offs of each major investment. Maintain clear records of product decisions, system behavior, and experiment findings. Make this knowledge easy for teams to find and use. Plan experiments and define success measures with Analytics and Data Science. Assess whether system changes produce incremental business value and recommend what to expand, change, or stop. Improve dashboards, alerts, and operational workflows so teams can detect problems early, assess system health, and reduce manual work. What You've Done: Required: Experience owning technical products, internal platforms, or automated decision systems. You can explain your product decisions, your delivery role, and the business results. Required: Ability to work through complex technical problems with Engineering and Data Science. You can trace data flows, discuss APIs and system dependencies, and assess implementation trade-offs. Experience managing a roadmap and backlog, setting priorities, and coordinating delivery across teams. You can balance business value, technical constraints, and available capacity. Strong commercial judgment. You can connect changes in system behavior to revenue, profit, cost, and operating efficiency, and