June Andrews talks about simple, cost-effective algorithmic computing at scale.
June Andrews is a data scientist at Pinterest working on enabling data-driven products and insights. Previously, she worked as technical lead of consumer analytics and staff data scientist at LinkedIn specializing in growth, engagement, and social network analysis. June’s work connected the global and local effects between LinkedIn’s professional network and individual members. She also worked on the search algorithm at Yelp, created the data analysis stack for Noom, a healthcare startup, and designed algorithms for computing the structure of large networks with John Hopcroft. June holds degrees in applied mathematics, computer science, and electrical engineering from UC Berkeley and Cornell.