Sr. Data Scientist, Performance Marketing

About Pinterest

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.

Role

We are looking for a Senior Data Scientist to join our marketing org. As a Senior Data Scientist you introduce greater scientific rigor into the marketing measurement and optimization processes to shape Pinterest’s user growth and marketing strategy. The results of your work will influence and drive strategic decisions for the company - identify investment opportunities for growth, understand user growth and behavior, and define metrics to grow and sustain our user base. You will collaborate on a wide array of business problems with a diverse set of cross-functional partners across Marketing, Product, Engineering, Design, Research, Product Analytics, Data Engineering and others.

The role is within the Growth Marketing team, and would be supporting performance marketing efforts focused on driving user growth for Pinterest.

What you’ll do

• Deep strategic analysis to answer growth marketing ecosystem questions such as how to drive monthly active users from paid performance marketing, how to quantify the effect of paid performance marketing in new markets, how to drive user engagement and user LTV (lifetime value) from performance marketing.
• Evolve our existing systems like geo-testing frameworks and other incrementality testing frameworks.
• Build and deploy statistical and machine learning models such as propensity, forecasting, and lifetime value (LTV) models—to optimize marketing strategies and enhance audience targeting.
• Develop new statistical models as well as maintain/improve existing models like user lifetime value models, budgeting models, long term user retention models etc.
• Collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Analytics, Marketing, Data Engineering and others.
• Evolve our experimentation capabilities and tools to evaluate the business impact of performance marketing investment. Advise on experimentation best practices; identifying flaws in experiment practices and results; building tools for experiment analysis; etc.
• Identify the right measures of success for teams and help them track those metrics. Own the full lifecycle of those metrics from logging requirements, metrics definition, prototype pipelines, and improvements.
• Translate complex analytical findings into clear, actionable insights and strategic recommendations for both technical and non-technical stakeholders, including senior leadership.
• Write clear, actionable analyses that help teams uncover opportunities and identify areas of improvement to our existing strategies.