Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA
June Andrews

June Andrews
Principal Data Scientist, Wise / GE Digital

Website | @Dr_June_Andrews

June Andrews is a Principal Data Scientist at Wise/GE Digital working on a machine learning and data science platform for the Industrial Internet of Things, which includes aviation, trains, and power plants. Previously, she worked at Pinterest spearheading the Data Trustworthiness and Signals Program to create a healthy data ecosystem for machine learning. She has also lead efforts at LinkedIn on growth, engagement, and social network analysis to increase economic opportunity for professionals. June holds degrees in applied mathematics, computer science, and electrical engineering from UC Berkeley and Cornell.


11:00am11:40am Thursday, March 16, 2017
Data science & advanced analytics
Location: LL21 A Level: Beginner
June Andrews (Wise / GE Digital), Frances Haugen (Pinterest)
Average rating: *****
(5.00, 5 ratings)
An experiment at Pinterest revealed somewhat shocking results. When nine data scientists and ML engineers were asked the same constrained question, they gave nine spectacularly different answers. The implications for business are astronomical. June Andrews and Frances Haugen explore the aspects of analysis that cause differences in conclusions and offer some solutions. Read more.