Jason Lam

Jason Lam has a strong background in natural language processing and machine learning, with experience in various roles since 2017. Jason is currently working as a Natural Language Processing & Machine Learning Engineer at Hireguide. Previously, they worked as a Machine Learning Engineer at BenchSci from December 2020 to August 2021.

Before that, they were an Artificial Intelligence Researcher at Conflict Analytics Lab from January 2019 to April 2021, where they developed machine learning and NLP models for predicting reasonable notice. Jason has publications in NLLP-KDD, ICML-LML, and McGill Law Journal Vol 65.

Jason also worked as a Research Scientist at Brandeis University from May 2020 to December 2020. Jason was a Quantitative Financial Modeling Consultant at CIBC from January 2020 to December 2020.

In addition, they worked as a Technical Consultant at Smith School of Business at Queen's University from May 2019 to September 2020. During this role, they guided and led students in the Queen's Masters of Management in Artificial Intelligence program and worked with corporate partners on machine learning and deep learning projects.

Furthermore, Jason has experience as a Research Assistant at Calian Group from May 2018 to December 2019, and as an Intern at Hazy Research Group - Stanford University from June 2017 to February 2018, where they achieved state-of-the-art results in biomedical entity-linking using weakly-supervised machine learning.

Jason Lam received their Bachelor of Education degree from Queen's University in 2018. After that, they pursued a Master of Science degree in Computer Science at Queen's University from 2018 to 2020. In 2017, they also had the opportunity to be a Visiting Graduate Student at Stanford University. Jason has obtained additional certifications, including passing the CFA Examination Level 1 from the CFA Institute in December 2019 and becoming an Ontario Certified Teacher in September 2018, certified by the Ontario College of Teachers.