Staff Data Scientist - Acquisition

StubHubLos Angeles, CA
21dHybrid

About The Position

We’re seeking a Staff Data Scientist 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 to 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.

Requirements

  • 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 Haves

  • Strong experience with SEM optimization and bidding, particularly from the ad-buyer side.
  • 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.

Responsibilities

  • 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.

Benefits

  • 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.

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Education Level

No Education Listed

Number of Employees

1,001-5,000 employees

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