Developed and implemented a comprehensive analysis tool using Python, pandas, NumPy, and SciPy, incorporating advanced statistical methods (e.g., Q-Q plots) to optimize heat pump performance. This tool supported predictive reliability models and achieved annual savings of approximately €800,000.Enhanced predictive maintenance systems by creating machine learning algorithms with scikit-learn, leading to a 15% improvement in system efficiency and a measurable reduction in scope 2 emissions.Designed and built full-stack architectures for industrial research applications, seamlessly integrating front-end and back-end systems with machine learning models to enhance operational workflows for heat pump data analysis.

Designed and implemented an automated reporting system using Python and VBA within the Digital Finance Department for a premium automotive manufacturer, enabling accurate evaluation of financial metrics across a €12 million portfolio.Conducted in-depth market trend analyses in the automotive sector, delivering actionable insights that shaped investment strategies and reduced reporting times by 70%.Streamlined data workflows by collaborating with cross-functional teams, enhancing decision-making processes for senior stakeholders and improving operational efficiency.