Stephanie Fitchett
About Stephanie Fitchett
Stephanie Fitchett is a Principal Data Scientist at FINRA, where she has worked since 2022. She holds a PhD in Mathematics from the University of Nebraska-Lincoln and a Master's degree in Statistics from Colorado State University, with extensive experience in predictive machine learning models and teaching statistics and mathematics.
Work at FINRA
Stephanie Fitchett has been serving as a Principal Data Scientist at FINRA since 2022. In this role, she applies her expertise in data science to enhance the organization's analytical capabilities. Her responsibilities include developing predictive machine learning models and conducting complex data analyses to support FINRA's regulatory mission.
Education and Expertise
Stephanie Fitchett holds a Master of Science in Statistics from Colorado State University and a Doctor of Philosophy in Mathematics from the University of Nebraska-Lincoln. Her academic background provides a strong foundation in statistical methods and mathematical principles, which she leverages in her professional work. She possesses proficiency in programming languages such as R, Python, and SQL, enabling her to perform advanced data analysis and visualization.
Background
Before joining FINRA, Stephanie Fitchett accumulated extensive experience in data science roles. She worked at Transamerica from 2017 to 2022, initially as a Data Scientist and later as a Lead Data Scientist and Principal Data Scientist. Her earlier experience includes a position as a Statistician at Neptune and Company, Inc. from 2013 to 2017, where she developed her skills in statistical analysis and data interpretation.
Teaching Experience
Stephanie Fitchett has academic experience teaching both statistics and mathematics. This teaching background complements her data science expertise, allowing her to effectively communicate complex concepts and methodologies to students and colleagues alike.
Professional Skills
Stephanie Fitchett is experienced in building predictive machine learning models, performing complex data analysis, and conducting data visualization. Her skills in statistical inference further enhance her ability to derive insights from data, making her a valuable asset in any data-driven environment.