Taylor Miller
Data Scientist
Summary
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RockstarTaylor Miller is a Data Scientist with 14 years of hands-on experience applying engineering discipline to analytics and healthcare problems. They combine data engineering skills with applied modeling to empower analytic teams, with notable open-source contributions to the widely used Great Expectations project where they scaffolded expectation suites and improved input handling for table schemas. Endlessly curious and maker-minded, Taylor bridges the gap between reproducible data quality practices and production-ready pipelines. Comfortable contributing to both code and team workflows, they focus on practical, auditable solutions that scale in healthcare settings. An underappreciated strength is their ability to translate data-quality improvements into faster downstream model iteration and more reliable insights.
14 years of coding experience
Github Skills (3)
great-expectations10
data-engineering10
python10
Programming languages (11)
Github contributions (5)
great-expectations/great_expectations
May 2019 - Jul 2021
Always know what to expect from your data.
Role in this project:
Data Engineer
Data EngineerContributions:5 releases, 160 reviews, 511 commits in 2 years 2 months
Contributions summary:Taylor's commits primarily focused on creating and modifying an Expectation Suite within the Great Expectations framework. Their work involved scaffolding directories and related notebook templates, and configuring various aspects of the project. The user also made changes to input handling, including fixing issues with the table column names.
pythondatadata-integritydatacleanerpipeline-testing
HealthCatalyst/healthcareai-py
Nov 2016 - Mar 2018
Contributions:4 releases, 146 commits, 187 PRs in 1 year 4 months
python-toolspythonhealthcaremachine-learning
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