I am a data enthusiast and end-to-end developer of complex, Cloud-Native, global software solutions in an environment of backend engineering, analytics and Big Data. My interdisciplinary skill set reaches from software development to dev-ops to data science and machine learning. My thorough hands-on experience in global teams with IBM and Mercedes-Benz is built upon numerous projects to build data-driven products, high throughput APIs and collection, storage, preparation and analysis of data to make valuable predictions and support decisions.
Many of my skills are self-taught on evenings and weekends. The internet has taught me about the command line, building websites, building RESTful APIs, getting comfortable with git, writing programs with Python, creating free Add-on nodes for SPSS Modeler and analyzing data with pandas, skikit learn and numpy. I read everything about Docker on a beach in Cuba with an app that allowed me to download websites. Ever since I have been a heavy user of the software and teach others how to use it. That again helped me to get into the Cloud-Native space and I learned everything about Kubernetes and Helm. I constantly try to further educate myself. (All links lead to examples of my work).
I graduated with a B.Sc. in business information technology from the Cooperative State University Stuttgart in Germany.
I have worked on a great variety of projects in various roles. They all were data driven and software development centric. I have been a data science consultant with IBM for many large corporations like Daimler, Continental, Porsche, Bosch, Fiducia. I have been a software developer with Mercedes, my startup energy-smart, as well as for open-source software. I worked as a backend engineer for Mercedes-Benz in Silicon Valley. For all the details of the projects publicly available, head over to my Linked In page, where I keep an up-to-date list of my projects.
If you're interested in my professional and educational history, you can take a look at my resumé here.