Laura Cotton is a software engineer with a decade of experience blending security-focused systems work and data-driven engineering, currently contributing at Audible. Her background includes research and tooling for secure infrastructure at Johns Hopkins APL and practical experience building web interfaces, databases, and virtualization workflows. After a decade spent prioritizing STEM-focused homeschooling and running a small music instruction business—during which she maintained a responsive website—she’s eager to return to full-time development with refreshed perspective and project-driven discipline. She also has hands-on data science and visualization experience, contributing to high-profile COVID-19 analysis visualizations, and brings strong foundations in algorithms and discrete mathematics from Georgia Tech.
10 years of coding experience
6 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Georgia Institute of Technology
Data analysis and visualizations of daily COVID cases report
Role in this project:
Data Scientist
Contributions:10 commits, 1 PR, 8 pushes in 4 months
Contributions summary:Laura's contributions primarily involve data analysis and visualization of COVID-19 case data. They load and process data from external sources, convert and format the data, and merge confirmed cases with death data. The user aggregates data for specific countries and then performs data transformations to calculate days since the first confirmed cases and creates visualizations using Plotly to display mortality rates. They focus on providing the data for the visualization of the project.
Contributions:89 pushes, 2 branches, 3 issues in 2 years 2 months
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