Richard Ugba
Software Engineer at Helmut Schmidt University, Hamburg
Hamburg, Germany
Summary
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SeniorRichard Ugba is a software engineer and data scientist based in Hamburg with eight years of hands-on experience building predictive models, machine learning pipelines, and analytics solutions in R and Python. He holds a BSc, MSc, and PhD in Statistics and a specialized certification from the University of Göttingen, which underpin his rigorous approach to experimental design and statistical validation. His background spans algorithmic trading strategy development, advanced statistical methods, and production-ready ML implementations, blending research-grade rigor with pragmatic software development. Comfortable with tools from JASP and SPSS to modern scripting languages, he routinely translates complex data questions into actionable models and reproducible workflows. Colleagues describe him as a researcher-turned-engineer who bridges theoretical depth with product-focused delivery. Quietly, he favors clarity and reproducibility in code and analysis, making him a reliable partner for data-driven decision making.
8 years of coding experience
Github Skills (12)
goodness-of-fit9
categorical8
logistic-regression8
journal7
open-access7
duplicates6
academia6
creative-commons5
dub5
nim-language3
smooth3
cli2
Programming languages (1)
Github contributions (5)
ejikeugba/serp
Dec 2020 - Nov 2024
Smooth Effects on Response Penalty for CLM
Contributions:7 releases, 4 PRs, 265 pushes in 4 years
nim-languagedubpenaltyduplicatessmooth
ejikeugba/gofcat
Dec 2021 - Aug 2022
Goodness-of-fit tests for categorical response models
Contributions:3 releases, 47 commits, 2 PRs in 7 months
goodness-of-fitlipsitz-testlogistic-regressionordinal-regressionbrant-test
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