Matthew Deakos
About Matthew Deakos
Matthew Deakos is a Senior Machine Learning Engineer with extensive experience in machine learning and data analysis. He has worked for various companies, including Udacity, Paystone, and PDFTron Systems, and holds a Master of Science in Computer Science from Georgia Institute of Technology.
Work at Paystone
Matthew Deakos has been employed at Paystone as a Senior Machine Learning Engineer since 2021. In this role, he focuses on developing advanced machine learning models and solutions that enhance the company's operational capabilities. His work includes implementing high-availability systems and mentoring junior engineers, contributing to the overall growth and expertise within the team.
Previous Experience at Udacity
Before joining Paystone, Matthew worked at Udacity as a Machine Learning Consultant from 2017 to 2020. During his tenure, he provided guidance on machine learning projects and helped students and professionals enhance their skills in this field. His experience at Udacity contributed to his expertise in practical applications of machine learning.
Background in Machine Learning Engineering
Matthew has a solid background in machine learning engineering, having worked at PDFTron Systems Inc. as a Machine Learning Engineer in 2021. He designed and led the transition of an internal AI site builder powered by large language models from prototype to full product. His technical skills include developing scalable models and implementing semantic search engines.
Education and Expertise
Matthew holds a Master of Science in Computer Science from the Georgia Institute of Technology, which he completed from 2019 to 2020. He also earned a Bachelor of Business Administration in Finance from the Lazaridis School of Business & Economics at Wilfrid Laurier University, graduating in 2017. His educational background provides a strong foundation for his work in machine learning and data analysis.
Achievements in Data Analysis
Matthew has conducted significant work in data analysis, including a causal impact analysis of reviews on customer acquisition using the dowhy package. He has also developed and maintained a schema for a Graph Database using neo4j and deployed it via Kubernetes, enhancing data storage and retrieval capabilities. His contributions have led to improved precision and recall in machine learning models.