Pinterest is looking for a Staff Data Scientist to shape the future of people-facing and business-facing products by solving complex engineering challenges related to user engagement and monetization.
Requirements
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.
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.
Responsibilities
Develop a deep, nuanced understanding of the Pinterest engagement ecosystem and key product surfaces, quantifying ecosystem-level opportunities and risks.
Lead projects on: Tradeoffs between organic engagement and advertising.
Deep dives on how engagement metrics impact monetization and retention.
Understanding and predicting the value of core behaviors (e.g., saving, repinning, board creation) as they relate to downstream business outcomes.
Designing and evaluating interventions that sustainably boost enterprise metrics across product boundaries.
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.
Other
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.
This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
This position is not eligible for relocation assistance.
