Alexander Grimm is a Senior Data Scientist based in Hamburg with seven years of experience building end-to-end ML and AI systems that move from stakeholder discovery to production delivery. He specializes in Databricks, Azure, PySpark and infrastructure-as-code, and has driven cloud-native, scalable solutions for retail and manufacturing including predictive maintenance and article performance prediction. Recently he’s focused on agentic AI—designing LLM-based systems with tool use that go beyond RAG to handle complex tasks autonomously. Comfortable both in client-facing product ownership and low-level debugging, he bridges business ambiguity and robust technical implementation to ensure models deliver real value in production. His background includes academic research in session-based recommender systems and hands-on Kubernetes monitoring work, which underpin a pragmatic, observability-minded approach to ML reliability. Always curious, he prefers doing his best work somewhere with better weather.
7 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at The Julius Maximilians University of Würzburg
Master's degree, Computer Engineering, Master's degree, Computer Engineering at Universidad de Granada
Contributions:1 release, 4 PRs, 144 pushes in 1 year 8 months
gcpcloud-computingcloudkubernetescomputing
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