Sr. Data Scientist

Pinterest Job Advertisements • New York, NY

15d • $226,089 - $287,749 • Remote

About The Position

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Requirements

• Master's degree (or a foreign equivalent) in Finance, Data Science, or a related field and three (3) years of experience in the job offered or in a related position.
• Advanced SQL proficiency for large-scale data analysis in distributed data warehouse environments such as Presto, Spark SQL, and Hive.
• Strong Python proficiency for large-scale data analysis and modeling, including the use of pandas, NumPy, stats models, and scikit-learn, as well as building robust analysis pipelines and production-ready notebooks or scripts.
• Deep expertise in applied machine learning and algorithmic modeling, including model development, evaluation, and optimization for real-world product use cases.
• Expertise in designing and analyzing online experiments for product changes, including power analysis, variance reduction, guardrail design, and heterogeneous treatment effect analysis on key metrics.
• Ability to structure ambiguous product questions into clear analytical roadmaps and deliver recommendations with quantified impact, risks, and assumptions.
• Expertise in causal inference for observational analyses, including methods such as propensity score matching/weighting and difference-in-differences, to estimate incremental impact and control for confounding factors.
• Experience defining and governing metrics and instrumentation, including event taxonomy, deduplication rules, attribution windows, metric specifications, data contracts, and lineage, to ensure consistency and reliability.
• Experience building scalable dashboards and automated insight-generation workflows to monitor core metrics, surface anomalies, and deliver stakeholder-ready insights for cross-functional partners.
• Experience conducting funnel and ecosystem analyses to identify bottlenecks, quantify trade-offs, and prioritize high-leverage product opportunities.
• Experience performing segmentation and cohort analyses to understand differences in engagement and retention, and to inform targeted interventions.
• Experience building clustering and segmentation models to identify meaningful user segments and usage scenarios.
• Strong statistical modeling and inference skills to quantify effects, measure uncertainty, and communicate statistical significance appropriately.

Responsibilities

• Deep strategic analysis to answer core business and operational questions including assessing the trade-off between metrics change, evaluating overall impact of changes of ads ecosystem.
• Write clear, actionable data and business analyses that help teams identify areas of improvement and investment.
• Build segmentation models to assess supply to inform pricing strategy.
• Improve decision velocity and quality using data scientist tool kit as well as experimentation, causal inference techniques.
• Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results including building tools for experiment analysis.
• Identify the right measures of success for engineering teams and help them track those metrics.
• Break down high-level metrics into actionable segments, including spanning from collecting entirely new datasets to building dashboards to track components of a metric (e.g., monitoring conversion data for missing values, implausible values, duplicated data).

What This Job Offers

• Job Type: Full-time
• Career Level: Senior