Jonatan Kallus
Machine Learning Research Engineer at Kognic
Gothenburg, Västra Götaland County, Sweden
Summary
👤
Senior🎓
Top SchoolJonatan Kallus is a Machine Learning Research Engineer with 16 years of experience combining rigorous statistical research and production-grade engineering. With a PhD background in mathematical statistics from Chalmers, he focuses on methods for analyzing high-dimensional and real-time data and translates those methods into scalable systems. At Kognic and previously at Recorded Future he built efficient aggregation, clustering and visualization pipelines that served tens of thousands of users and 20k+ daily alerts, owning everything from architecture to UX. His career spans academia and fast-moving startups, giving him fluency in DevOps, data engineering and algorithm design. Jonatan’s practical curiosity shows in rapid language uptake and system integrations—from building A/B and queuing frameworks to delivering timeline visualizations—reflecting a talent for turning complex data into usable products. Based in Gothenburg, he blends deep math with hands-on software craft to tackle high-dimensional, real-world problems.
17 years of coding experience
5 years of employment as a software developer
Bachelor and Master, Engineering Mathematics, Complex Adaptive Systems, Bachelor and Master, Engineering Mathematics, Complex Adaptive Systems at Chalmers tekniska högskolaDoctor of Philosophy - PhD, Mathematical Statistics, Doctor of Philosophy - PhD, Mathematical Statistics at Chalmers University of Technology
Stackoverflow
283reputation
6kreached
2answers
4questions
Github Skills (28)
csharp8
engine7
real-time-strategy7
dotnet7
potree7
xmonad6
lisp6
haskell6
functional-programming6
gnome6
ffi6
feed6
fedora6
linux6
xfce6
Programming languages (6)
Github contributions (5)
kallus/soc
Dec 2016 - Jan 2018
Contributions:11 pushes in 1 year
kallus/mmpca-figures-tables
Nov 2019 - Feb 2020
Contributions:1 push, 1 branch in 3 months
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