About Megan Church:
I graduated from William & Mary in May 2023, earning a B.S. in Data Science and Psychology with a concentration in Data Application. I recently completed an internship with the U.S. Department of Education’s Institute of Education Sciences, where I worked on cleaning and querying grant data to inform Congress of IES-funded publications and created various data visualizations and dashboards.
Data visualization is my passion!!
In my free time, I like to “do data.” For example, I have created several interactive dashboards, visualizations, spreadsheets, and databases related to my personal life. My current favorite is a database and dashboard combination, detailing all the concerts I have attended.
I recently completed an internship with the U.S. Department of Education’s Institute of Education Sciences, where I worked on cleaning and querying grant data to inform Congress of IES-funded publications and created various data visualizations and dashboards. I also received impractical requests from non-data science professionals and would use my knowledge to suggest alternate approaches that were well-received and achieved the same goals.
Additionally, I was a research assistant at William & Mary’s School of Education, looking at how elementary-aged students interact with and learn about data. I co-authored “Appearing and Disappearing in the Data: Emotional Configurations within Children’s Data Modeling Practices,” and conducted independent research focusing on how children accept zero as a finding. Both projects involved intensive literature reviews, coding video data, and wrangling unstructured data.
I graduated from William & Mary in May 2023, earning a B.S. in Data Science and Psychology with a concentration in Data Application. My coursework covered everything from statistical modeling and machine learning to research methods and natural language processing. Due to my interest in data visualization, I have also taken several classes to build my visualization skills; these include Cognitive Psychology, Foundations of Learning and Memory, Network Science, and Agent-Based Modeling.
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