Staff Data Scientist, Engagement Ecosystem

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.

Track record mentoring and growing data talent at the staff/senior IC level.

Develop a deep, nuanced understanding of the Pinterest engagement ecosystem and key product surfaces, quantifying ecosystem-level opportunities and risks.

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.