Ari Hartikainen
Senior Data Scientist
Espoo, Mainland Finland
Summary
🤩
Rockstar🎓
Top SchoolAri Hartikainen is a Senior Data Scientist based in Espoo with a decade of experience blending geophysics and Bayesian statistics to solve real-world problems. Currently at Lumo Analytics and pursuing doctoral research at Aalto University, he bridges academic rigor in geological/geophysical engineering with practical analytics for industry. As a core developer for Stan and ArviZ Python projects, he contributes backend improvements to widely used Bayesian tooling—work that improves model interfacing, summaries, and visualization for the broader probabilistic modeling community. His background ranges from field geology and nuclear waste statistical analysis to highway engineering, giving him uncommon domain depth for data-driven modeling. Comfortable refactoring complex scientific code and improving numerical displays and APIs, he brings both reproducible research practices and production-minded engineering to Bayesian workflows. Colleagues value his ability to translate geophysical insight into robust statistical implementations that scale beyond research into applied analytics.
10 years of coding experience
1 year of employment as a software developer
Master of Science (MSc), Geological/Geophysical Engineering, Master of Science (MSc), Geological/Geophysical Engineering at Aalto UniversityFinnish Matriculation Examination, Finnish Matriculation Examination at Porkkala upper secondary school
Github Skills (14)
data-analysis10
mathematical10
bayesian10
stan10
python10
modeling10
testing10
xa9
apidoc9
api9
statistics9
xray9
c-language8
cprogramming-language8
Programming languages (12)
Github contributions (5)
stan-dev/pystan2
Oct 2016 - Feb 2021
PyStan, the Python interface to Stan
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 2 reviews, 179 commits in 4 years 5 months
Contributions summary:Ari primarily worked on the backend of the PyStan library, focusing on core functionality and API improvements. Their contributions involved refactoring the `api.py` module, including changes to how model names are handled and how UTF-8 characters are encoded. The user added new test files to validate the functionality of the package. Furthermore, the user improved the summary output of the StanFit4Model object with new functions and methods, along with updated docstrings and example code.
python-interfacestanpythonpystan
arviz-devs/arviz
Jan 2017 - Dec 2022
Exploratory analysis of Bayesian models with Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:6 releases, 195 reviews, 249 commits in 5 years 11 months
Contributions summary:Ari primarily focused on refactoring and improving the ArviZ library, converting functions using `round` to string formatting and improving the HPD and ROPE display. The user also worked on the utility functions, refactoring the data reading procedure and modifying the plotting code to adapt for numerical value display. The user contributed towards code quality with several commits focused on minor enhancements.
pythonexploratorybayesian-inferencemachine-learningbayesian-models
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