Chiara Marmo
Senior Pedagogical Software Engineer at oudeis.io
France
Summary
🤩
Rockstar🎓
Top SchoolChiara Marmo is a senior pedagogical software engineer with 19 years of experience blending research-grade scientific software development, technical writing, and education-focused tooling. Based in France, she has shaped user-facing features in JupyterLab, improved core geospatial and astronomy libraries like GDAL and Astropy (notably on FITS/WCS support), and polished documentation across NumPy and scikit-learn. Her background as a research engineer and PhD-trained astronomer enables her to translate complex scientific requirements into reliable code, tests, and clear learning materials. Equally comfortable in TypeScript front-ends and C/Python back-ends, she often bridges gaps between developer experience, reproducible research, and pedagogy. An under-the-radar strength is her consistent work on testing and documentation infrastructure, which has measurably improved onboarding and long-term maintainability for major open-source projects.
18 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Università degli Studi di Padova
English, French, Italian, Spanish
Github Skills (27)
markdown10
c-language10
restructuredtext10
python10
raster10
sphinx10
gdal10
typescript10
geospatial10
jupyterlab10
wcs10
spatial-data10
numpy10
fits10
astropy10
Programming languages (16)
Github contributions (5)
scikit-learn/scikit-learn
Sep 2019 - Dec 2022
scikit-learn: machine learning in Python
Role in this project:
Technical Writer
Technical WriterContributions:366 reviews, 124 commits, 245 PRs in 3 years 4 months
Contributions summary:Chiara primarily contributed to improving the project's documentation. They fixed sphinx warnings and inconsistencies, addressed issues with references and links, and updated formatting for better readability. The user also reorganized installation instructions and made adjustments to the layout of documentation pages such as the "testimonials" and "authors" sections. These modifications show an effort to enhance the clarity and user experience of the scikit-learn documentation.
data-analysispythonstatisticsdata-sciencelearn-machine-learning
astropy/astropy
Dec 2020 - Dec 2022
Astronomy and astrophysics core library
Role in this project:Technical Writer & Test Automation Engineer
Technical Writer & Test Automation EngineerContributions:105 reviews, 74 commits, 33 PRs in 2 years
Contributions summary:Chiara primarily contributed to improving documentation and examples related to the `astropy.io.fits` module. They focused on clarifying usage examples, particularly related to header verification, checksum verifications, and VLA tables. Additionally, the user made significant changes to testing infrastructure, including using the `SHOW_WARNINGS` directive and added tests for core functionality.
astrologypythonscienceastrophysicsastrodynamics
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.