Jillian Greene brings an analytical, data-focused approach to her work. As an analyst at Cadeo, Jillian tackles large and complex datasets. In particular, she enjoys diving into highly quantitative datasets. She is skilled at summarizing data in a way that is easily digestible by both technical and nontechnical audiences. Jillian has a strong skillset in many data-focused Python toolsets and packages. These include Pandas, NumPy, and Scikit-Learn for processing and analyzing the data and Seaborn, Plotly, and Matplotlib for visualizing the data.
At Cadeo, Jillian’s work focuses on providing insights from data about post-weatherization energy usage, electric vehicle concentration, and nonresidential lighting market trends. She excels at using a mix of data analysis techniques, statistical methods, and machine learning.
Before joining Cadeo, Jillian was a researcher at the Applied Research Institute under the University of Illinois College of Engineering. She contributed to several projects that allowed her to gain experience in machine learning, image processing, and artificial intelligence. Jillian has a BS in Mathematics from the University of North Texas. She also has an MS in Mathematics from Washington University in St. Louis. In her free time, you can find Jillian curled up with her dog and a good book, exploring nature, or cooking something overly ambitious for dinner.