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# Staff Data Scientist, Ads Delivery

- **Company:** Pinterest
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $164,695.0 - $339,078.0
- **Contract:** Permanent contract
- **Skills:** Data Infrastructure, Experimental Data, Python (Programming Language), Machine Learning, Usage Analysis, Sql Optimization, Apache Spark, Information Technology
- **Published:** August 4, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17810807?backUrl=%2Fcareer%2F17810807%2FStaff-Data-Scientist-Ads-Delivery-California-San-Francisco

## About the Role

* 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.
 * Bachelor's/Master's degree in a relevant field such as Computer Science, or equivalent experience

## Description

* Develop a deep, nuanced understanding of the Pinterest ads delivery, quantifying full funnel opportunities and risks.
 * Lead projects on: 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.


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