Merel Theisen
Principal Software Engineer II at QuantumBlack, AI by McKinsey
Amsterdam, North Holland, Netherlands
Summary
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Rockstar🎓
Top SchoolMerel Theisen is a Principal Software Engineer II based in Amsterdam with a decade of experience building resilient data and machine-learning infrastructure. At QuantumBlack (McKinsey) she leads teams and products in Kedro, serving as the tech lead for the open-source Kedro framework and contributing significant full-stack and back-end work to kedro-viz and kedro itself. Her contributions span CI stability, Windows E2E fixes, GraphQL run-tracking, performance-focused refactors, and deployment documentation—practical improvements that make ML pipelines more reliable in production. She combines hands-on engineering across Python, DevOps, and CI/CD with leadership roles including Diversity & Inclusion Lead, showing a blend of technical depth and people-focused stewardship. Merel’s background includes systems work at Schibsted and Mendeley, giving her broad experience with data pipelines, distributed systems, and cloud platforms. Colleagues describe her as a pragmatic problem-solver who elevates open-source projects by fixing hard edge cases that commonly break real-world deployments.
10 years of coding experience
10 years of employment as a software developer
Gymnasium Sciences, Gymnasium Sciences at Gymnasium FelisenumBSc Exchange U21 Computer Science & Information Technology, BSc Exchange U21 Computer Science & Information Technology at University of NottinghamBachelor of Science (hons) Liberal Arts & Sciences, Bachelor of Science (hons) Liberal Arts & Sciences at Amsterdam University CollegeUniversity College London
English, Dutch, French
Stackoverflow
61reputation
731reached
5answers
0questions
Github Skills (29)
data-visualizations10
python10
apidoc10
data-visualisation10
wpgraphql10
cicd10
kedro10
api10
wordpress-graphql10
experiment10
graphql10
error-handling10
data-visualization10
react10
testing9
Programming languages (6)
Github contributions (5)
kedro-org/kedro
Jul 2020 - Jan 2023
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:12 releases, 1819 reviews, 141 commits in 2 years 7 months
Contributions summary:Merel primarily contributed to improving the stability and usability of the Kedro project. They focused on fixing end-to-end tests on Windows, introducing try-catch blocks and retry mechanisms to handle potential errors. The user also added documentation related to single-machine deployment. Further contributions involved refactoring and refactoring code, as well as upgrading dependencies and adjusting the testing suite.
experiment-trackingpythonsciencepipelinedata-science
kedro-org/kedro-viz
Aug 2020 - Jan 2023
Visualise your Kedro data and machine-learning pipelines and track your experiments.
Role in this project:Full-stack Developer
Full-stack DeveloperContributions:215 reviews, 43 commits, 30 PRs in 2 years 5 months
Contributions summary:Merel primarily worked on enhancing the functionality and maintainability of the `kedro-viz` project. Their contributions include fixing the Windows CI environment setup, refactoring codebase, and renaming default endpoints in the server-side API. Furthermore, the user added GraphQL resolvers for run queries and implemented run tracking data fetching. The user also contributed to the project's compatibility with `kedro-datasets` and improved the codebase for enhanced performance.
experiment-trackingpythonreactkedro-plugindata-science
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