Jing Zhang

Senior Applied Research Engineer

About

Jing Zhang is a Senior Applied Research Engineer on the Impact Team. Jing brings expertise in machine learning and distributed system design. He designs and builds software prototypes and products in our thesis areas. In addition, he develops infrastructure to improve the efficiency of machine learning research and experimentation.

Experience

Jing previously worked at Amazon as a Software Engineer where he designed and developed a large-scale data platform that feeds a machine learning system to predict defect locations and track inventory quality. Prior to Amazon Jing worked at Kiribatu Labs as a Data Scientist working on an auto-insurance risk score prediction model.

Education

Jing holds a Master of Science in Computing Science from the University of Alberta and a Bachelor of Engineering specializing in Information Engineering from Beijing University of Posts and Telecommunications.

Did you know?

Outside work Jing enjoys cooking. When he’s not eating the food he cooks, he turns it into art with his camera. Jing can also be found behind his camera taking travel and portrait shots.

Contact Jing

(416) 868-9696

Areas of Expertise

Software Engineering

Cloud Computing

Machine Learning

Distributed System Design

Devops

Companies

True Fit

True Fit is a data-driven personalization platform for footwear and apparel retailers. Hosting the industry’s most comprehensive data collective True Fit uses advanced AI technology to map the detailed style, fit, and technical attributes from clothes and shoes to the detailed preferences of millions of individual shoppers.

Team: Justin LaFayette, Michael Robinson

Signpost

Signpost is automated CRM for B2C businesses. The Signpost platform automatically tracks every email, call, credit card transaction and social media interaction between a business and one of its customers. Signpost’s automated marketing engine leverages this CRM data to send email and SMS messages that convert new customers and drive repeat business and word-of-mouth.

Team: Tyson Baber, Justin LaFayette, Michael Robinson, Emily Walsh