Wiktor Olszowy is a Senior Data Scientist with 10 years of experience applying production-grade machine learning across life sciences, from computational chemistry and virtual screening to industrial time-series models for manufacturing. He builds end-to-end, reproducible ML systems—deploying models via CI/CD on AKS/Argo, tracking artifacts with MLflow, and emphasizing interpretability (SHAP) so chemists and engineers can trust and act on predictions. He has a strong academic grounding (PhD, Cambridge) in quantitative imaging and signal processing, which informs his rigorous approach to experiment design, uncertainty quantification, and artifact modelling. Beyond project work he shapes platform and engineering standards—co-leading company-wide Share & Learn sessions on security and tooling and driving a migration to GitHub—helping teams adopt robust, auditable workflows. Skilled in Python, TensorFlow/PyTorch and applied NLP/sensor analytics, he combines deep-domain curiosity with a pragmatic focus on operational robustness and clear documentation for non-ML stakeholders.
10 years of coding experience
9 years of employment as a software developer
High School, High School at High School No. 3 in Gdynia, Poland
Doctor of Philosophy (Ph.D.) Clinical Neurosciences, Doctor of Philosophy (Ph.D.) Clinical Neurosciences at University of Cambridge
Master’s Degree Statistics, Master’s Degree Statistics at Ludwig-Maximilians-Universität München
Bachelor’s Degree Economics with Mathematics, Bachelor’s Degree Economics with Mathematics at Humboldt-Universität zu Berlin
Contributions:4 pushes, 1 branch in 1 year 2 months
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