Data Scientist, Creator Content at Pinterest
San Francisco, CA, US

About Pinterest:

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.

Pinterest is seeking a data scientist who's interested in dealing with questions relating to content quality, relevance, audience engagement and social networking, all key to establishing a healthy content ecosystem on Pinterest. The ideal candidate will have industry experience in developing recommendation systems and shipping ML models that boost user engagement. You’ll apply quantitative analysis, modeling and data mining to improve our pinners’ and partners’ experience.

What you’ll do:

  • Perform deep dive analysis of acquired and internal content quality signals
  • Understand recommendation systems that rank candidate content in users feeds. 
  • Think about creator concerns to inform signal development and design 
  • Build and understanding of the economics of supply and demand of content within Pinterest’s ecosystem
  • Design and interpret human evaluation tasks to build out truth sets for modeling
  • Work with product managers and engineers to design data products and run and analyze A/B experiments

What we're looking for:

  • 6+ years of industry experience with proven ability to apply scientific methods to solve real-world problems on web-scale data
  • Expert in at least one scripting language (Python/R)
  • Proficient in SQL/Hive
  • Proven ability to perform rigorous data analysis and translate the results into business recommendations.
  • You are knowledgeable in one or more of the following: machine learning, recommendation systems, social network analysis, computer vision or NLP