Nathan Cheng

Nathan Cheng has worked in the technology industry since 2013. In 2013, they worked as a Failure Analyst at AFCC Automotive Fuel Cell Cooperation Corp. (AFCC). In 2014, they were a Research Intern at the Max-Planck Institute for Solid State Research in Stuttgart, Germany. In 2019, they joined Ravelin Technology, where they have held various roles. Nathan began as a Junior Data Scientist, developing Tensorflow serving platforms for low-latency predictions and deep learning models for fraud prevention. Nathan then moved to a Data Scientist role, developing dbt tooling for analysts and data scientists, working with in-memory databases and BigTable for low-latency machine learning feature access, and developing a random-walk software algorithm on a real-time graph database. Nathan is currently Director of Detection and a Senior Data Scientist, line managing data scientists and machine learning engineers, leading low-latency NLP model research and product implementations, and leading proof of concepts to develop machine learning solutions for preventing online fraud.

Nathan Cheng attended The University of British Columbia from 2011 to 2016, where they received a Bachelor's Degree in Mathematics and Physics. In 2016, they returned to The University of British Columbia to pursue a Master's Degree in Condensed Matter and Materials Physics, which they completed in 2018. During their Master's Degree, they also spent time as a Visiting Student at the Max Planck Society, studying Condensed Matter and Materials Physics.