Sr. Data Scientist, Performance Marketing

Pinterest•San Francisco, CA

8d•Remote

About The Position

Pinterest is seeking a Senior Data Scientist to join its Growth Marketing team and bring scientific rigor to marketing measurement and optimization. The role supports performance marketing efforts focused on user growth. Its work will inform strategic company decisions, including growth investment opportunities, understanding user growth and behavior, and defining measures to grow and sustain Pinterest’s user base. The Data Scientist will work with cross-functional partners across Marketing, Product, Engineering, Design, Research, Product Analytics, and Data Engineering. The position involves analyzing growth marketing questions, developing and improving statistical and machine learning models, and advancing experimentation and incrementality measurement. The role also owns the lifecycle of success metrics, translates analyses into actionable recommendations for technical and non-technical audiences, and builds dashboards, reporting tools, and ETL pipelines that support data-driven decisions.

Requirements

At least 5 years of combined post-graduate academic and industry experience applying scientific methods to real-world problems.
Master’s degree in a quantitative field such as mathematics, statistics, computer science, or engineering.
Hands-on experience building marketing measurement solutions to quantify the business impact of marketing tactics and investments.
Strong background in statistics and quantitative analysis, including applying advanced statistical techniques to real-world problems.
Expertise in at least one scripting language, ideally Python or R.
Proficiency in SQL/Hive and ability to write efficient SQL queries.
Strong business and product sense.
Ability to turn vague questions into well-defined analyses and success metrics that drive business decisions.
Excellent communication skills, including communicating findings to leadership and cross-functional teams and explaining work and thought processes clearly and concisely.
Experience leading key technical projects.
Strong experimentation background and statistical rigor.
Experience with causal inference projects.

Responsibilities

Conduct strategic analyses of growth marketing questions, including paid marketing’s effect on monthly active users, performance marketing in new markets, user engagement, and user lifetime value.
Evolve geo-testing and other incrementality testing frameworks.
Build and deploy statistical and machine learning models, including propensity, forecasting, and lifetime value models, to optimize marketing strategies and audience targeting.
Develop new statistical models and maintain or improve existing models, including user lifetime value, budgeting, and long-term user retention models.
Collaborate with cross-functional partners on product and business problems.
Improve experimentation capabilities and tools for evaluating the business impact of performance marketing investment; advise on experimentation best practices, identify flaws in practices and results, and build experiment analysis tools.
Identify appropriate success measures for teams and manage their full lifecycle, including logging requirements, metric definitions, prototype pipelines, and improvements.
Translate analytical findings into clear, actionable insights and strategic recommendations for technical and non-technical stakeholders, including senior leadership.
Write actionable analyses that help teams identify opportunities and areas for improvement in existing strategies.
Design, maintain, and promote dashboards and automated reporting tools for self-serve, data-driven decision-making.
Build and optimize ETL data pipelines to automate reporting, support deep-dive analysis, and enable feature engineering for analytical models.