Greater Bern Area
• Scientific staff at Federal Office of Public Health • External lecturer at ETH Zürich and Uni Bern • 20+ years of experience in statistics and ML • Former jobs in insurance pricing, medical statistics, finance, consulting • Python | R | SQL • Git | Databricks | Fabric | Spark • Author of several Python and R packages: LightSHAP, missRanger, shapviz, kernelshap, confintr and more • ML Blog with Christian: https://lorentzen.ch/index.php/blog/ • Kaggle competition and notebook expert • Top 2% contributor on https://stats.stackexchange.com Publicly available lecture notes • Statistical Computing at University of Bern: https://github.com/mayer79/statistical_computing_material • Responsible ML with insurance applications at ETH Zurich: https://github.com/lorentzenchr/responsible_ml_material • Webinar available both in Python and R: https://github.com/mayer79/ml_lecture • Statistics for students of social and economic sciences at University of Bern: https://github.com/mayer79/Statistikskript_WiSo
"Responsible Machine Learning with Insurance Applications" at the Math Department of the ETH Zurich. Jointly with Christian Lorentzen.
Teaching "Statistical Computing" for master students in Statistics and Data Science, see details here: https://www.math-stat.unibe.ch/studium/lehrveranstaltungen/fruehjahr_2023/master_statistics_and_data_science/statistical_computing_fs_2023/index_ger.html
Lecturer for continuing studies in statistics (linear models)
Lecturer in introductory statistics for students of the economic and social sciences
Non-life pricing actuary (motor). Working with technologies including Python, Spark, Databricks, Azure, Git.