Luke Dyer
Senior Product Manager at Peak
Calderdale, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolLuke Dyer is a Senior Product Manager and former machine learning lead with a decade of experience turning advanced mathematics and data science into production AI products at Peak. With a PhD in Mathematics from the University of Edinburgh and a strong applied background in R&D, he has progressed from hands-on data scientist to product leadership while retaining deep technical fluency. His open-source contributions to the widely used Great Expectations project show practical expertise in data ingestion and reliability—improving S3/file connectors and compressed-file handling that directly benefit ML pipelines. Based in Calderdale, he combines research-grade modeling skills with product instincts to bridge data engineering, model development, and customer-facing outcomes.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Mathematics, Doctor of Philosophy - PhD, Mathematics at The University of EdinburghClitheroe Royal Grammar School and Sixth FormMaster's degree, Mathematics, 1st, Master's degree, Mathematics, 1st at University of Warwick
Github Skills (15)
aws-s310
pandas10
aws10
data-pipeline10
amazon-s310
data-pipelines10
python10
s3-bucket10
data-engineering10
data-quality9
data-connectors9
data-connector9
cli8
data-cleaning7
testing7
Programming languages (4)
Github contributions (5)
great-expectations/great_expectations
Feb 2021 - Feb 2022
Always know what to expect from your data.
Role in this project:
Data Engineer
Data EngineerContributions:3 reviews, 8 commits, 8 PRs in 11 months
Contributions summary:Luke contributed significantly to improving data connector configurations, particularly for S3 and file-based data sources. They addressed issues with reading compressed files (e.g., .csv.gz) and added functionality to allow reader options in the CLI, enabling more flexible data loading. Furthermore, the user refactored tests and fixed bugs related to handling S3 data, demonstrating a focus on improving the reliability and functionality of data ingestion pipelines. The user also worked on refactoring and bug fixes related to pandas read functions.
pythondatadata-integritydatacleanerpipeline-testing
luke321321/inversemcmc
Dec 2017 - Nov 2018
Contributions:100 commits, 3 pushes, 3 branches in 11 months
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