David Lopez is a supervisory data scientist with seven years of experience turning complex program metrics into actionable insights for federal agencies, including the U.S. Department of Labor, GSA, and the Forest Service. He blends HR and training expertise with developing backend data systems—contributing to the Galaxy Project—so he understands both people-centered metrics and scalable data workflows. Known for designing performance measurement frameworks, strategic plans, and stakeholder-tailored reporting, he bridges the gap between operational needs and technical solutions. Currently finalizing a Computer Science degree while leading data teams, he pairs practical government program knowledge with hands-on backend development for data-intensive scientific applications.
7 years of coding experience
2 years of employment as a software developer
Bachelor's Degree, Computer Science, 3.0, Bachelor's Degree, Computer Science, 3.0 at Trident University International
Contributions:1195 reviews, 121 commits, 620 PRs in 3 months
Contributions summary:David's contributions primarily involve back-end development, as seen in the modification of Python scripts related to task management, notification systems, and database interactions within the Galaxy project. They worked on improving and expanding the existing functionality of the system by adding features, addressing bugs, and refining the code. The commits show modifications to internal processes such as code linting, improving data handling and adding new features like API calls or the functionality to handle the state of a given task, indicating an expertise in backend development for data-intensive scientific applications.
Contributions:2 reviews, 4 PRs, 1694 pushes in 4 years 6 months
intensivepythonsciencedata-science
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