Summary
Kyrylo Medianovskyi is a Data Scientist at Swedbank with a decade of experience applying interpretable machine learning, uncertainty estimation, and causal inference to credit risk and AML model QA. He builds IRB validation software and production-ready tooling using Python (Spark, EconML, polars, MLflow), SAS, and Teradata SQL, bringing a strong mix of research-grade methods and production engineering. His background includes web visualization and IoT-focused research at the University of Tartu, where he improved event-detection F1 and automated NN fine-tuning to cut computation time by 25%. Comfortable across statsmodels and plotting stacks as well as React frontends, he bridges model interpretability with auditable delivery in regulated finance. A dual-degree applied mathematics and computer science graduate, he combines rigorous quantitative foundations with practical system-building for high-stakes ML.
10 years of coding experience
2 years of employment as a software developer
Master's degree, Computer Science, GPA 4.57, Master's degree, Computer Science, GPA 4.57 at University of Tartu
Igor Sikorsky Kyiv Polytechnic Institute