Max Zwiessele
Senior Data Scientist
Brugherio, Lombardy, Italy
Summary
🤩
Rockstar🎓
Top SchoolMax Zwiessele is a Senior Data Scientist with 14 years’ experience applying machine learning and production-grade engineering to healthcare and financial products, currently seeking remote roles around Milano. He holds a PhD in Machine Learning for Personalized Medicine and combines deep academic expertise with hands-on experience in Python, TensorFlow, PyTorch, Spark, Kafka and multi-cloud deployments across AWS, GCP and Azure. At Babylon Health he moved models from research into production, and now drives data-driven products at FE fundinfo with end-to-end ownership from ETL and feature engineering to algorithm optimization and product integration. An active contributor to the SheffieldML GPy Gaussian processes project, he has improved testing, robustness and plotting support—showing attention to reproducibility and tooling beyond model code. Colleagues value his collaborative approach to iterative improvement and his emphasis on observing live systems to unlock continuous AI gains.
14 years of coding experience
10 years of employment as a software developer
Master of Science - MS, Bioinformatics, Master of Science - MS, Bioinformatics at University of TübingenDoctor of Philosophy - PhD, Machine Learning for Personalized Medicine, Doctor of Philosophy - PhD, Machine Learning for Personalized Medicine at The University of Sheffield
Github Skills (3)
unit-testing10
python10
testing10
Programming languages (7)
Github contributions (5)
SheffieldML/GPy
Mar 2013 - Jul 2019
Gaussian processes framework in python
Role in this project:
Backend & Test Engineer
Backend & Test EngineerContributions:11 releases, 2127 commits, 203 PRs in 6 years 5 months
Contributions summary:Max's commits primarily focus on enhancing the testing infrastructure and improving the core functionality of the GPy framework. The contributions involve implementing new tests for addressing specific issues and functionalities, as well as fixing parameters inside the init. They also correct mixed noise var dtc, refactoring code, and ensuring that unit tests pass for several existing modules within the library. Additionally, the changes extend to supporting different plotting libraries.
gaussiangaussian-processespython
MC-Notes/Volume-I
Oct 2016 - Mar 2017
Contributions:8 PRs, 161 pushes, 15 branches in 4 months
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