Summary
Péter Pölös is a Senior Data Scientist based in Copenhagen with six years of experience turning statistical rigor and economic insight into production-ready AI solutions. Trained in Mathematics and Economics at the University of Copenhagen, he combines strong quantitative modelling with practical engineering—Python, R, SQL and containerized deployment on Azure/Terraform—to ship LLM-powered products, churn models and geo-clustering analytics. He has driven AI adoption as part of Centers of Excellence, running workshops, scoping high-impact use cases and building MLOps platforms using Databricks, MLflow, Kubernetes and CI/CD. Notably, he fine-tuned image-generation models to align with brand identity and operationalized feedback-insight and support-training chatbots, showing a rare blend of creative ML and business-facing delivery. Colleagues describe him as structured, analytically curious and committed to continuous learning of state-of-the-art data science techniques.
6 years of coding experience
6 years of employment as a software developer
Master of Science - MS Mathematics and Economics, Master of Science - MS Mathematics and Economics at Københavns Universitet - University of Copenhagen
Finance General, Finance General at Heller Farkas College of Advanced Financial Studies
Bachelor of Science - BS Economic and Financial Mathematical Analysis, Bachelor of Science - BS Economic and Financial Mathematical Analysis at Corvinus University of Budapest
English, Hungarian, Spanish