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PinterestPinterestSeattle, WA

Staff Data Scientist, Ads Delivery

Lead data science projects on ads delivery, LTV, and engagement tradeoffs. Design ML frameworks, drive experimentation, and mentor scientists. Requires 10+ years experience and deep expertise in ML, causal inference, and product analytics.

165k – 339k
Hybrid10+ YOEData Science

About the role

What you’ll do:

  • Develop a deep, nuanced understanding of the Pinterest ads delivery, quantifying full funnel opportunities and risks.
  • Lead projects on:
    • Pinner LTV
    • Tradeoff between ads and organic engagement
    • Ads Delivery opportunities across different funnel stages
  • Design and productionize robust, scalable ML and evaluation frameworks—spanning forecasting, recommendation, and causal inference.
  • Advocate for best-in-class experimentation, instrumentation, and metric design; bridge the gap between short-term proxy metrics and long-term business impact.
  • Collaborate across disciplines—Product, Engineering, Research, Business, and Design—translating complex data questions into actionable business insights.
  • Mentor and guide junior and senior scientists, fostering intellectual curiosity and driving technical excellence.

What we’re looking for:

  • 10+ years of hands-on experience in web-scale data environments, with a track record of solving hard, ambiguous problems in product, engagement, or ecosystem analytics.
  • Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.
  • Deep expertise in: Machine Learning (recommendation, ranking, prediction, experimentation), Statistical Modeling & Causal Inference (observational and experimental data), Product analytics/strategy (beyond dashboards: root cause, goaling, design collaboration), Programming in Python/R and advanced SQL/Spark.
  • Strong product intuition—ability to scope, question, and design the right solutions for ill-defined, high-impact business problems.
  • Scientific rigor and healthy skepticism: You challenge assumptions, find flaws, and drive towards robust, reproducible outcomes.
  • Exceptional communication: You make the complex simple, and can influence both technical and non-technical audiences.
  • Track record mentoring and growing data talent at the staff/senior IC level.
  • Cross-functional leadership and the ability to align competing interests towards shared goals.

Skills

Machine LearningRecommendation SystemsRanking AlgorithmsCausal InferenceStatistical ModelingExperimentationPythonRSQLSpark

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