Pavel Sůva

Pavel Sůva has extensive work experience in data science and credit risk analysis. Pavel currently works at Datamole as a Data Science Team Lead, where they manage a team of data scientists and guides the data science aspects of various projects. Pavel is also actively involved in a project involving time series classification and signal processing. Prior to this role, they worked at Home Credit International as a Senior Data Scientist, applying AI/ML models in the agricultural industry. Pavel contributed to the development of the Lely Pretreatment Optimizer and created comprehensive monitoring dashboards. Before that, Pavel worked as a Data Science Team Lead in the Risk R&D department at Home Credit International, where they focused on data science tooling and developed a Python library for credit scoring. Pavel also worked as a Senior Data Scientist in the Risk Research & Development team, transitioning expert-based decisioning processes into data-driven mathematical models. Additionally, Pavel served as Senior Credit Risk Analyst and Credit Risk Analyst, overseeing underwriting processes and implementing strategy changes using the Fico Blaze Advisor decision engine. Prior to their time at Home Credit International, Pavel worked at Raiffeisenbank Česká republika as a Credit Risk Analyst, managing underwriting policies and conducting quantitative analyses. Pavel also worked as a Junior Business Analyst, contributing to the development of a new datamart for regulatory reporting.

Pavel Sůva obtained their Bachelor's degree in General Mathematics from Charles University during the period of 2006 to 2009. Pavel continued their education at the same university and earned a Master's degree in Probability theory, mathematical statistics, and econometrics from 2009 to 2011. Prior to attending Charles University, Pavel attended Gymnázium Omská from 1998 to 2006, though no specific degree or field of study was mentioned.