Michael Groff
About Michael Groff
Michael Groff is a Data Scientist with a strong background in machine learning and expertise in multiple programming languages. He has worked in the financial services industry and currently serves at LSQ in Orlando, Florida.
Work at LSQ
Michael Groff has been employed at LSQ as a Data Scientist since 2020. In this role, he has applied his expertise in data science to various projects within the financial services industry. Prior to his current position, he worked at LSQ as a Risk & Data Intern from 2019 to 2020, where he gained valuable experience in data analysis and risk assessment. His work at LSQ is based in the Orlando, Florida area.
Education and Expertise
Michael Groff holds a Bachelor of Science in Computational Mathematics from the University of Central Florida, where he studied from 2014 to 2018. He furthered his education by obtaining a Master of Science in Computer Science from the Georgia Institute of Technology, completing this program in 2019. His academic background has equipped him with strong skills in multiple programming languages, including Java, C#, Python, and Matlab, as well as a solid foundation in machine learning.
Background
Michael Groff has a demonstrated history of working in the financial services industry. His professional journey includes a role as a Graduate Intern Engineer at The Coca-Cola Company for three months in 2019. This experience, combined with his internships and current position at LSQ, has provided him with a comprehensive understanding of data science applications in various sectors.
Machine Learning Focus
During his Master’s degree at the Georgia Institute of Technology, Michael Groff focused on machine learning. This specialization has informed his approach to data science, allowing him to leverage advanced analytical techniques in his current role. His expertise in machine learning enhances his ability to develop data-driven solutions and insights.
Technical Skills and Tools
Michael Groff is proficient in several programming languages, including Java, C#, Python, and Matlab. He utilizes Google Cloud Platform extensively in his data science projects, enabling him to manage and analyze large datasets effectively. His technical skills support his work in data analysis and machine learning, contributing to his success in the financial services industry.