In our talk, we describe the small and large pitfalls that can occur in the life of a data scientist.
Coming from the "safe space" of the university, where you can tinker around in your own Git repository, you suddenly have to work with many other people in your everyday work. "Hell, that's the others," says Sartre. Well, maybe it's not quite that bad. Nevertheless, it makes sense to deal with the different perspectives and expectations of all those involved.
How do I communicate with platform architects and data protection officers? What do I have to consider when contacting customers? What do my superiors expect from me – and I from them? Am I allowed to make mistakes? What tools and procedures help with collaboration?
Using concrete examples, we show why data scientists have to be able to do much more than analyze data and write code. And why exactly that's what makes the job so exciting.