At Lidl Hungary, I build end-to-end analytical and machine learning solutions in Databricks, from ETL pipelines to forecasting and supply chain optimization. I also analyze store KPIs, perform clustering analyses, and build web-scraping pipelines for strategic insights.
Previously, I improved K&H Bank's KATE chatbot through Python development, internal tooling, training-data analysis, and hyperparameter optimization that increased model performance by approximately five percentage points. At Yettel Hungary, I worked on churn prediction, social network analysis of call records, PySpark models, and complex SQL extraction.
I also contributed to network-science research on depression spread across more than 300,000 individuals and advised financial-services clients at Mastercard Advisors on projects totaling €700M in revenue.
