Michael Davis
Senior Associate Software Engineer
Virginia, United States
Summary
🤩
Rockstar🎓
Top SchoolMichael Davis is a Senior Associate Software Engineer at Capital One with eight years of experience building data-driven applications and tooling. He holds a B.S. in Software Engineering from Iowa State University and has a strong interest in AI and machine learning, demonstrated by academic research replicating deep quantification networks. Michael contributes to prominent open-source data-quality projects like great_expectations and Capital One’s DataProfiler, where he improved data profiling, serialization, and test coverage—work that highlights expertise in data quality and profiler integrations. His background spans full-stack and systems work—from React/TypeScript portals and NLP-driven search to C/C# simulation tooling—showing an ability to move between research, production services, and low-level integration. Based in Virginia, he pairs practical enterprise experience with open-source impact, often focusing on reliability and measurable performance gains.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Software Engineering, Bachelor of Science - BS, Computer Software Engineering at Iowa State University
Github Skills (15)
data-analysis10
unit-testing10
pandas10
great-expectations10
data-quality10
unit-test10
python10
data-science10
data-profiling10
data-engineering10
testing10
debug9
debugging9
machine-learning8
json8
Programming languages (3)
Github contributions (5)
capitalone/DataProfiler
Mar 2022 - Jan 2023
What's in your data? Extract schema, statistics and entities from datasets
Role in this project:
Data Scientist & QA Engineer
Data Scientist & QA EngineerContributions:4 releases, 399 reviews, 30 commits in 9 months
Contributions summary:Michael primarily contributed to the `dataprofiler` project by fixing bugs, and reformatting code. The user addressed issues related to JSON serialization and data profiling. They also enhanced the test coverage by integrating json.dumps() functionality and updated the numerical statistics and datetime functionalities. Additionally, the user improved test coverage across multiple profiler classes and also added testing for the new load and save functionality for the graph profiler.
csvpythondatanpistatistics
great-expectations/great_expectations
Nov 2022 - Nov 2022
Always know what to expect from your data.
Role in this project:Data Engineer
Data EngineerContributions:8 reviews, 2 commits, 5 PRs in 1 day
Contributions summary:Michael contributed to the data profiling and expectation framework within the project. Their work focused on integrating the DataProfiler, specifically for structured and float data types, by adding new rules and modifying existing ones. They were involved in fixing import issues related to Capital One contributions and in defining new expectations, thereby improving data quality analysis. These contributions indicate expertise in data quality and potentially integration with data profiling tools.
pythondatadata-integritydatacleanerpipeline-testing
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