Marco Gorelli
Senior Software Engineer at Quansight
Cardiff, Wales, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolMarco Gorelli is a Senior Software Engineer based in Cardiff with eight years of experience blending data science and backend engineering, currently focusing on pandas development at Quansight. He has a strong open-source track record across flagship Python projects—NumPy, pandas, scikit-learn, Plotly, Black and Altair—contributing everything from type-hinting and CI fixes to documentation and probabilistic modelling examples. His background in Bayesian methods and probabilistic programming (PyMC, NumPyro) complements hands-on work improving data tooling performance and interoperability (Polars, pandas timezone/date parsing). Marco holds a master’s in Mathematics and Foundations of Computer Science from Oxford and brings a meticulous, test-driven approach that often surfaces in subtle but impactful fixes, like improving example plots, notebook support, and dependency handling for broader compatibility.
8 years of coding experience
5 years of employment as a software developer
Master's degree, Mathematics and Foundations of Computer Science, Master's degree, Mathematics and Foundations of Computer Science at University of Oxford
Github Skills (66)
notebook10
datetime10
probabilistic-programming10
datetime-parsing10
python10
bayesian-data-analysis10
testing10
refactor10
mcmc10
automation10
pymc10
blackboard10
linter10
refactoring10
visualizations10
Programming languages (15)
Github contributions (5)
pandas-dev/pandas
Aug 2019 - Jan 2023
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:
Data Scientist & QA Engineer
Data Scientist & QA EngineerContributions:3353 reviews, 261 commits, 1290 PRs in 3 years 5 months
Contributions summary:Marco's contributions primarily focused on identifying and fixing bugs related to data processing and data type handling within the pandas library. They addressed issues such as incorrect parsing of date strings, and incorrect handling of mixed timezone objects. The user also contributed to improving the robustness and consistency of the to_datetime function and contributed to the correction of several test failures related to the interchange protocol.
pythondatalabeled-datamanipulationdataframes
pymc-devs/pymc-examples
Dec 2020 - Sep 2021
Examples of PyMC models, including a library of Jupyter notebooks.
Role in this project:Data Scientist
Data ScientistContributions:37 reviews, 16 commits, 31 PRs in 9 months
Contributions summary:Marco contributed to the PyMC3 examples repository by moving and refactoring existing notebooks, likely for improved organization and maintainability. The user fixed incorrect entries in a table of contents and removed outdated information, which indicates a focus on ensuring the project's usability and accuracy. Furthermore, the user re-ran and updated notebooks for various models including regression analysis, demonstrating proficiency in applying Bayesian methods and working with existing examples.
pythonpymcjupyter-notebooknotebooksjupyter
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