Staff Machine Learning Engineer - Acquisition Paid Search

Job Description

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.

About the Opportunity

We're seeking a Staff Machine Learning Engineer to lead the science and systems that power our paid search marketing. You'll design the causal measurement stack, ship models that influence bidding and budgeting in real time, and partner with marketing, data, and platform teams to drive profitable, incremental growth.

StubHub is the largest secondary ticket market in the world, generating massive amounts of consumer data that are leveraged to tackle many unique and interesting predictive and inference problems across user acquisition, product recommendations, pricing optimization, ticket fulfillment mitigation, and business forecasting. The core challenge for our marketing efforts is acquire as many new customers as possible, efficiently, and at the right time in their customer journey, making it a complex and highly impactful domain.

Location : Hybrid (3 days in office / 2 days remote) – New York, NY or Los Angeles, CA

What You'll Do :

• Own causal measurement for paid search : Stand up uplift / incrementality frameworks (e.g., doubly robust learners, causal forests, DML, IVs, synthetic control, DiD, BSTS) to quantify lift beyond correlation.
• Ship production models : Build and serve models that inform bids, budgets, and query-level targeting using signals like incremental CPA, tROAS, LTV, and heterogenous treatment effects.
• Design experiments & guardrails : Architect geo / cell tests and online experiments; handle power analysis, pre-trend checks, SUTVA threats, SRM detection, and sequential monitoring.
• Integrate with ad platforms : Translate science into APIs / feeds for Google Ads, Microsoft Advertising, and SA360; validate against auction dynamics and Quality Score mechanics.
• Data & MLOps leadership : Partner with platform teams to instrument events, build reliable feature stores and ETL (batch / stream), and establish monitoring for drift, bias, leakage, and attribution sanity.
• Mentor & influence : Provide technical leadership across science, engineering, and marketing; set standards for methodology, code quality, documentation, and reproducibility.
• Tell the story : Communicate trade-offs and impact to execs and non-technical partners; make the complex understandable and actionable.

What You've Done :

Nice to Have :

Staff-Level Capabilities

What We Offer :

The anticipated gross base pay range is below for this role. Actual compensation will vary depending on factors such as a candidate's qualifications, skills, experience, and competencies. Base annual salary is one component of StubHub's total compensation and competitive benefits package, which includes equity, 401(k), paid time off, paid parental leave, and comprehensive health benefits.

Salary Range

$300,000—$350,000 USD

About Us

StubHub is the world's leading marketplace to buy and sell tickets to any live event, anywhere. Through StubHub in North America and viagogo, our international platform, we service customers in 195 countries in 33 languages and 49 available currencies. With more than 300 million tickets available annually on our platform to events around the world from sports to music, comedy to dance, festivals to theater StubHub offers the safest, most convenient way to buy or sell tickets to the most memorable live experiences. Come join our team for a front-row seat to the action.

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We are an equal opportunity employer and value diversity on our team. We do not discriminate on the basis of race, color, religion, sex, national origin, gender, sexual orientation, age, disability, veteran status, or any other legally protected status.