Develop a deep, nuanced understanding of 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.
Requirements
10+ years of hands‑on experience in web‑scale data environments.
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.