Summary
Strehl Thomas is a pragmatic data scientist and DevOps-savvy architect with nine years of experience at IBM, blending machine learning, data engineering and MLOps to move models from research into production. He has led projects across fraud detection, COVID-19 analytics, career-prediction for migrants and data lineage automation for large DWHs, using R, Python, SQL, GitLab, DVC and Kubernetes. His background running a SoftLayer-based Cloud DataCenter and work as a DevOps Architect give him rare end-to-end fluency in cloud, monitoring and automation alongside statistical modeling. Notable for building an interactive COVID dashboard and a REST-based ML pipeline PoC, he excels at bridging academic collaboration and enterprise delivery. Based in Vienna, he pairs a formal grounding in data engineering and physics with practical skills in performance testing and observability to deliver reliable, explainable data products.
9 years of coding experience
7 years of employment as a software developer
Vienna University of Technology
Physics, Physics at University of Vienna
German, English