Eero Siivola
Senior Data Scientist
Finland
Summary
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Rockstar🎓
Top SchoolEero Siivola is a Senior Data Scientist with nine years of experience blending probabilistic machine learning research and practical applied work across academia, industry, and consultancy. He completed PhD-level research in Bayesian modelling at Aalto University and has translated that expertise into production and advisory roles, including co-founding Enne Analytics and publishing work from internships at Amazon and collaborations with Novartis. Eero has led method development teams at the Finnish Environment Institute and now solves customer problems using diverse ML techniques at Vuono Group. He is an active contributor to open-source Gaussian process tooling (notably improving Expectation Propagation in the GPy framework), reflecting a focus on robust inference and numerical reliability. Based in Finland, he combines deep theoretical grounding with hands-on engineering and a track record of turning complex probabilistic models into usable insights.
9 years of coding experience
9 years of employment as a software developer
Doctor's Degree Computer Science, Doctor's Degree Computer Science at Aalto UniversitySpecialist Vocational Qualification in Leadership and Business Management, Specialist Vocational Qualification in Leadership and Business Management at Helsinki Business College Oy
English, Finnish, Swedish
Github Skills (7)
gpy10
machine-learning10
inference10
python10
numpy10
gaussian-processes10
algorithms9
Programming languages (6)
Github contributions (5)
SheffieldML/GPy
Jun 2017 - Jun 2017
Gaussian processes framework in python
Role in this project:
ML Engineer
ML EngineerContributions:1 review, 6 commits, 6 PRs in 1 day
Contributions summary:Eero's commits focus on refactoring and enhancing the Expectation Propagation (EP) implementation within the GPy framework. Their work involves modifying the EPBase class, adding and updating methods for cavity parameter calculations and posterior computations. The changes directly impact the core inference mechanisms of Gaussian Processes within this library. The user's contributions suggest a focus on improving the efficiency and accuracy of the EP algorithm.
gaussiangaussian-processespython
esiivola/syke-machine-learning-course
Mar 2021 - Oct 2024
Contributions:1 review, 14 PRs, 43 pushes in 3 years 8 months
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