Ryan's expertise sits at the intersection of machine learning, product management, and climate change. Currently, he is focused on developing Natural Language Processing models that are being used to inform and drive the scalability of Manifest's climate change platform.
Prior to joining Manifest, Ryan co-founded Autocase, a climate change tech startup, where he acted as CTO and led a diverse product team consisting of economists, software developers, and web designers. Ryan was directly involved in the development of models used to quantify the benefits of sustainable infrastructure and green buildings.
After 4 years at Autocase, Ryan spent 3 years working as a Data Science Lead, including most recently at a Toronto AI startup called Integrate.ai. At Integrate, Ryan was a part of a machine learning research team and led the development of new machine learning approaches focused on solving marketing optimization problems for a range of Canada's largest companies.
Ryan holds a Bachelor's degree in Biology from Queen's University, an MBA from Dalhousie University, and loves to use cutting edge technology and machine learning to solve high-impact, real-world problems.