Michael Dalgleish
About Michael Dalgleish
Michael Dalgleish is a Data Science Manager at Enova International in Chicago, Illinois, with a background in economics and statistics from the University of Michigan. He has held various roles in data science and analytics across multiple companies, including positions as an Analyst, Trader, and Lead Data Scientist.
Current Role as Data Science Manager
Michael Dalgleish currently serves as a Data Science Manager at Enova International, a position he has held since 2021. In this role, he oversees data science projects and leads a team focused on leveraging data analytics to drive business decisions. His work involves developing data-driven strategies and implementing advanced analytical techniques to enhance operational efficiency.
Career at Enova International
Michael Dalgleish has had a significant tenure at Enova International, where he has held multiple roles. He began as an Analyst from 2016 to 2017, followed by a position as a Data Scientist from 2017 to 2019. He later advanced to Lead Data Scientist from 2019 to 2021 before assuming his current role. His progression reflects his expertise in data analysis and commitment to the company's objectives.
Previous Experience at Title Check LLC
Before joining Enova International, Michael worked at Title Check LLC as a Special Projects Consultant from 2015 to 2016. In this role, he contributed to various projects, applying his analytical skills to support the company's initiatives. His experience at Title Check LLC provided him with valuable insights into project management and consulting.
Background in Trading at Chopper Trading
Michael Dalgleish worked at Chopper Trading as a Trader from 2012 to 2015. During his three years in this role, he gained experience in financial markets and trading strategies. This background in trading has likely informed his analytical approach in subsequent roles within data science.
Education in Economics and Statistics
Michael Dalgleish earned a Bachelor of Science degree in Economics and Statistics from the University of Michigan, where he studied from 2008 to 2012. His educational background provides a strong foundation in quantitative analysis and economic theory, which supports his work in data science and analytics.