Staff Data Scientist, Engagement Ecosystem

Pinterest Pinterest · Consumer · San Francisco, CA · Core Engineering

Staff Data Scientist at Pinterest focused on the Engagement Ecosystem. The role involves developing and productionizing ML frameworks for forecasting, recommendation, and causal inference, applying advanced ML and generative AI techniques to model complex interactions, and championing responsible AI use. Requires expertise in ML, causal inference, experimentation, and large-scale data environments, with a track record of influencing product decisions and mentoring junior scientists.

What you'd actually do

  1. Develop a deep, nuanced understanding of the Pinterest engagement ecosystem and key product surfaces, quantifying ecosystem-level opportunities and risks.
  2. Design and productionize robust, scalable ML and evaluation frameworks—spanning forecasting, recommendation, and causal inference.
  3. Advocate for best-in-class experimentation, instrumentation, and metric design; bridge the gap between short-term proxy metrics and long-term business impact.
  4. Collaborate across disciplines—Product, Engineering, Research, Business, and Design—translating complex data questions into actionable business insights.
  5. Use advanced ML, causal inference, and generative AI techniques to model and explain complex interactions across the Pinterest ecosystem (e.g., organic engagement, ads, content quality, monetization), turning highly ambiguous business questions into clear, testable hypotheses and decision frameworks for Core and Monetization leadership.

Skills

Required

  • Machine Learning (recommendation, ranking, prediction, experimentation)
  • Statistical Modeling & Causal Inference (observational and experimental data)
  • Product analytics/strategy
  • Programming in Python/R and advanced SQL/Spark
  • Scientific rigor and healthy skepticism
  • Exceptional communication
  • Cross-functional leadership
  • Proven track record applying machine learning and/or causal inference to complex, ambiguous product or marketplace problems at scale
  • Hands-on experience with modern AI/ML tools and workflows (such as PyTorch, TensorFlow, scikit-learn, or similar, plus LLM-based assistants or copilots)
  • Masters degree in a technical field (e.g., Computer Science, Statistics, Mathematics, Engineering, Social Sciences)

Nice to have

  • Mentoring and growing data talent at the staff/senior IC level

What the JD emphasized

  • Use advanced ML, causal inference, and generative AI techniques to model and explain complex interactions across the Pinterest ecosystem
  • Apply AI-assisted analysis and developer tools (e.g., copilot, intelligent dashboards) to accelerate exploration, improve code quality, and scale insight generation
  • Champion responsible and scientifically rigorous use of AI across the ecosystem
  • Proven track record applying machine learning and/or causal inference to complex, ambiguous product or marketplace problems at scale
  • Hands-on experience with modern AI/ML tools and workflows (such as PyTorch, TensorFlow, scikit-learn, or similar, plus LLM-based assistants or copilots)

Other signals

  • Develop and productionize ML frameworks for forecasting, recommendation, and causal inference.
  • Apply advanced ML, causal inference, and generative AI techniques to model complex interactions.
  • Champion responsible and scientifically rigorous use of AI across the ecosystem.