Hakim Invernizzi
Data Scientist
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolHakim Invernizzi is a data scientist based in Zurich with a decade of hands-on experience building ML systems across industry and research, currently applying production-grade analytics at Digitec Galaxus. Trained at EPFL in Computer Science and Digital Humanities, he blends rigorous engineering with a human-centered perspective, having led a deep-learning entity-linking project on historical Japanese archives. He has worked client-side and in research labs, shipping end-to-end solutions from anomaly detection to time-series forecasting and contributing Transformer-based improvements to the popular open-source darts library. Comfortable with both prototype research and production deployments, he excels at translating domain questions into robust ML pipelines and clear stakeholder-facing insights.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Ecole polytechnique fédérale de Lausanne
Italian, French, English, German
Github Skills (8)
pytorch10
machine-learning10
deep-learning10
time-series-forecasting10
python10
data-science9
testing9
anomaly-detection9
Programming languages (1)
Github contributions (5)
unit8co/darts
Sep 2020 - Oct 2020
A python library for user-friendly forecasting and anomaly detection on time series.
Role in this project:
ML Engineer / Data Scientist
ML Engineer / Data ScientistContributions:12 reviews, 12 commits, 1 PR in 29 days
Contributions summary:Hakim contributed to the development and testing of a Transformer model within the `darts` library, focused on time series forecasting and anomaly detection. Their work involved adapting unit tests to accommodate the use of the Transformer model and adjusting example notebooks to reflect the updated method signatures. The user's primary contribution centered on adapting and improving the existing Transformer model, including multi-step forecasting support.
forecastingpython-libraryanomalypythontime-series-analysis
inverniz/few-shot
May 2019 - Sep 2019
Repository for few-shot learning machine learning projects
Contributions:12 commits, 10 pushes in 3 months
machine-learning-projectsdeep-learningshot-learningmachine-learningfew-shot
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