Alexander
Levin-Koopman
As a lecturer in Applied Data Science at the University of Michigan School of Information, I'm passionate about solving problems through insights extracted from complex data sets. With a Master's degree in Applied Data Science (4.0 GPA) from the University of Michigan and a Bachelor's degree in Mathematics from the University of Colorado at Boulder, I've developed a strong foundation in statistical analysis, machine learning, and data visualization.
My academic background has equipped me with a unique ability to approach problems from multiple angles, think creatively, and communicate complex ideas effectively. While my experience is rooted in academia, I'm eager to apply my skills in a real-world setting and drive business outcomes through data-driven decision making.
I thrive on solving intricate problems and uncovering hidden patterns in data. My goal is to leverage my expertise to inform strategic decisions, optimize processes, and create value for organizations. If you're looking for a driven and analytical problem-solver who is passionate about data science, let's connect!
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Vermont Lake Health Analysis
Project description: The focus of this project was to provides an analysis of lake water health in Vermont. The dataset contains decades of chemical tests of lake water across more than 400 lakes in the state. We combined chemical measurements data with land use survey data, population density, and geospatial data. Our goal was to understand how lake health has changed over time and with respect to geographic region and population growth. The determination of lake health was done through a derived metric that was based on the rate of change of chemicals present.
Figure 1: Health Metric and Land Use
Figure 2: Correlation Heatmap
Figure 3: Chemical Measurements and Population Over Time
