Erik Petrovski is a Lead Machine Learning Engineer in Copenhagen with nine years of experience applying quantitative sociology and production-grade ML to large public and private datasets. He builds end-to-end ML pipelines and infrastructure—using Azure DevOps, Kubernetes, Docker and Python—focused on customer outcomes and administrative cost reduction at a €50B pension fund. Trained as a PhD sociologist, he brings rigorous statistical thinking to model risk assessment and continuous-delivery practices, routinely embedding unit testing, version control and containerization into data products. Prior roles in government and academia include developing continuous risk scoring for tax/customs and forecasting public-sector labor needs, highlighting an uncommon blend of domain policy knowledge and engineering. He’s as comfortable with SQL and R for big-data analysis as he is productionizing ML, and he looks for automation opportunities that turn analytic insight into operational savings.
9 years of coding experience
6 years of employment as a software developer
Study visit, Sociology, Study visit, Sociology at Freie Universität Berlin
HTX, HTX at H.C. Ørsted High School
Master of Science (MSc), Sociology, 10.8 out of 12, Master of Science (MSc), Sociology, 10.8 out of 12 at University of Copenhagen
Doctor of Philosophy (Ph.D.), Sociology, Doctor of Philosophy (Ph.D.), Sociology at Roskilde University
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