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.
- 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:
- 8+ years in applied ML/causal inference (or equivalent) with direct paid search/auction experience.
- Expert in causal methods (uplift modeling, DML, IV, DiD/synth control, BSTS/Bayesian time series) and experimental design.
- Strong software engineering: Python (pandas, numpy, scikit-learn, LightGBM/XGBoost), SQL; experience with Spark and one of AWS/GCP/Azure.
- Hands-on with A/B frameworks, power analysis, and measurement diagnostics (SRM, balance, interference).
- Proven track record integrating with Google Ads/Microsoft Ads/SA360 and moving the needle on tROAS, CPA, LTV.
- Clear communicator who can mentor senior ICs and partner with product/marketing.
Nice to Have:
- Recsys, bandits/RL for bidding/budget pacing, MMM and privacy-aware attribution
- Scala/Java or microservices experience; Airflow/DBT; Kafka/PubSub; Feast or similar feature stores.
- Domain knowledge of auction theory, query taxonomy, brand vs. non-brand dynamics, and budget rebalancing
Staff-Level Capabilities
- Technical leadership through influence rather than formal management authority
- Strategic thinking with the ability to balance long-term technical vision with immediate organizational needs
- Cross-functional collaboration skills to work effectively with Data Science, Product, and Engineering teams
- Communication skills to inject technical context into high-level organizational discussions
- Problem-solving approach for ambiguous, high-impact technical challenges
- Mentorship and sponsorship experience growing junior and mid-level engineers
- Accelerated Growth Environment: Immerse yourself in an environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
- Top Tier Compensation Package: Enjoy a rewarding compensation package that includes enticing stock incentives, aligning with our commitment to recognizing and valuing your contributions.
- Flexible Time Off: Embrace a healthy work-life balance with unlimited Flex Time Off, providing you the flexibility to manage your schedule and recharge as needed.
- Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.
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.
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