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PinterestPinterestSan Francisco, CA

Staff Data Scientist, Ads Delivery

Leads quantitative analysis, experimentation, and machine-learning initiatives for Pinterest’s ads delivery systems. The role requires 10+ years of web-scale data experience, strong product intuition, cross-functional leadership, and expertise in causal inference, recommendation, and analytics.

165k – 339k/yr
Hybrid10+ YOEData Science

About the role

Responsibilities

  • Develop a deep, nuanced understanding of Pinterest ads delivery, quantifying full-funnel opportunities and risks.
  • Lead projects focused on ads delivery opportunities across different funnel stages.
  • Design and productionize robust, scalable machine learning and evaluation frameworks spanning forecasting, recommendation, and causal inference.
  • Advocate for best-in-class experimentation, instrumentation, and metric design; bridge short-term proxy metrics and long-term business impact.
  • Collaborate with Product, Engineering, Research, Business, Design, Product Analytics, and Data Engineering to translate complex data questions into actionable business insights.
  • Mentor and guide junior and senior scientists, fostering intellectual curiosity and technical excellence.

Requirements

  • 10+ years of hands-on experience in web-scale data environments, solving complex and ambiguous problems in product, engagement, or ecosystem analytics.
  • Deep expertise in machine learning, including recommendation, ranking, prediction, and experimentation.
  • Expertise in statistical modeling and causal inference using observational and experimental data.
  • Product analytics and strategy experience, including root-cause analysis, goal setting, and design collaboration.
  • Programming experience in Python or R and advanced SQL or Spark.
  • Strong product intuition and the ability to design solutions for ill-defined, high-impact business problems.
  • Scientific rigor, healthy skepticism, and a focus on robust, reproducible outcomes.
  • Exceptional communication skills with technical and non-technical audiences.
  • Experience mentoring and developing data talent at the staff or senior individual-contributor level.
  • Cross-functional leadership and the ability to align competing interests toward shared goals.
  • Bachelor's or master's degree in a relevant field such as Computer Science, or equivalent experience.

Compensation and Benefits

  • Base salary: $164,695–$339,078 USD.
  • Eligible for equity.
  • Benefits and culture information are available through Pinterest.

Skills

Machine LearningRecommendation SystemsrankingForecastingCausal InferenceStatistical ModelingExperimentationPythonRSQLSparkProduct AnalyticsData Modeling

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