Applied Economist, Ads Marketplace at Pinterest
San Francisco, CA, US

Millions of people across the world come to Pinterest to find new ideas every day. It’s where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. As a Pinterest employee, you’ll be challenged to take on work that upholds this mission and pushes Pinterest forward. You’ll grow as a person and leader in your field, all the while helping users make their lives better in the positive corner of the internet.

Within the Ads Quality team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. You will be responsible for developing and executing a vision for the evolution of the Pinterest marketplace. You will also design and implement online experiments that shape the utility function, ad allocation strategies, and lead multi-functional projects that improve the ads delivery funnel, derive new insights through analysis of the marketplace dynamics. In short, this is a unique position, where you’ll have the freedom to work across the organization to bring together Pinners and partners in this unique marketplace.

What you’ll do:

  • Build and improve auction mechanisms and marketplace utility functions to maximize value for Pinners, Partners and Pinterest.
  • Define and implement experiments to understand long term Marketplace effects
  • Develop yield management strategies to balance long and short term business objectives.
  • Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.

What we’re looking for:

  • Ph.D. degree in Economics, Statistics, Computer Science or related field
  • Strong mathematical skills with knowledge of statistical methods
  • Multi-functional collaborator and a strong communicator
  • 6+ years of related industry and/or academic experience
  • Hands-on experience with building large-scale online advertising, e-commerce and/or recommender auctions and ML systems.