Andrej Dvornik

Engineered scalable Python and Bash pipelines to manage and process over 1 million-object multidimensional datasets, automating visualisations, reducing dimensionality, and standardising statistical calculations for reproducible, high-quality scientific outputs. Developed a state-of-the-art cosmological modelling tool in Python, integrating numerical integration, differential equation solvers, regression, correlation analysis, and machine learning techniques.

Processed and analyzed over 1 PB of astronomical image data using a custom Python and SQL pipeline, leveraging distributed computing infrastructure and scalable storage solutions for efficient batch processing. Presented complex statistical analyses and data-driven insights at international scientific conferences and in peer-reviewed journals, translating raw data into accessible, compelling conclusions.