Summary
Johannes Schöck is a Senior Data Scientist with eight years of experience turning complex industrial and retail datasets into actionable solutions across semiconductors, automotive, chemicals and large-scale retail. He designs and ships end-to-end data products—from automated ETL pipelines and CI/CD-enabled data apps to predictive maintenance and store-turnover forecasting for 2,300 stores—while advancing MLOps and software engineering best practices. His background in applied physics and hands-on semiconductor research gives him uncommon depth in failure analysis and process optimization, applied to both lab-scale device data and production line telemetry. Comfortable with Python, Azure DevOps, low/no-code platforms and Power BI, he blends statistical rigor, clustering and algorithmic optimization with pragmatic tooling to accelerate business impact. Johannes is also an experimental practitioner who maintains a public portfolio and uses private projects to trial new techniques before production adoption.
8 years of coding experience
10 years of employment as a software developer
High School Diploma, Honors, High School Diploma, Honors at Tilton School
Dr. rer. nat., Engineering Physics/Applied Physics, Dr. rer. nat., Engineering Physics/Applied Physics at Friedrich-Alexander-Universität Erlangen-Nürnberg