Sr. Data Scientist, Performance Marketing

Pinterest•San Francisco, CA

8d•$139,764 - $287,749•Remote

About The Position

Pinterest is seeking a Senior Data Scientist to join its Growth Marketing team and support performance marketing efforts focused on user growth. The role applies scientific rigor to marketing measurement and optimization, shaping user-growth and marketing strategy. Its findings will inform strategic company decisions, including growth investment opportunities, user growth and behavior, and metrics to grow and sustain Pinterest’s user base. The position works with partners across Marketing, Product, Engineering, Design, Research, Product Analytics, and Data Engineering. The role is located anywhere in the United States, with in-office collaboration required 1–2 times per quarter. It is not eligible for relocation assistance. The US base salary range is $139,764–$287,749, and the position is also eligible for equity. Final salary depends on factors including location, travel, relevant experience, and skills and expertise.

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, including the ability to turn vague questions into well-defined analyses and success metrics that drive business decisions.
Excellent communication skills and ability to lead initiatives and communicate findings to leadership and cross-functional teams; able to explain work and thought processes clearly and concisely.
Experience leading key technical projects.
Strong experimentation background.
Statistical rigor and experience with causal-inference projects.

Responsibilities

Analyze growth-marketing questions, including how paid performance marketing can drive monthly active users, how it affects growth in new markets, and how it can increase user engagement and 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, maintain, and improve models such as 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 to evaluate the business impact of performance-marketing investment; advise on best practices, identify flaws in experiment practices and results, and build experiment-analysis tools.
Identify appropriate success measures and own their 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 improve 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.