Interning at SAP’s HQ in Germany
I spent three months as a Data Science / Machine Learning Intern with the Exponential Analytics team in SAP’s Walldorf headquarters.
This was an interesting and somewhat scary decision for me, since it was my first time working in a new country. It was reassuring to see, after just a few days at the office, the Walldorf office is extremely diverse with employees coming in from all over the world.
There are definitely some big differences between interning in the US vs. Germany, but most of them were actually outside of the office: pace of life (especially on Sundays when everything closes), food, extremely good public transportation, etc.
Within the office, and intrinsic to the field of data science, was a new challenge every single day. I was fortunate enough to have colleagues who were trusting and brought me onboard several projects. Many times, they were working with concepts, tools, or frameworks I was not familiar with, but being a quick learner is part of the role. Here are a few points that I’ll definitely take back home with me:
- Doing what you know first: Outlining project plans, writing pseudocode, or just writing down goals has been so helpful. It’s easy to translate logic to syntax, but it’s incredibly difficult to translate a vague idea to syntax.
- Efficiency is key: When the datasets are this big, just creating something that works is no longer good enough. It needs to be fast. I quickly learned efficiency is just as important as reaching the end goal.
- Becoming good at telling stories: Good data visualization is key. It also saves unnecessarily long emails. There’s no need to send several paragraphs of text when you can convey the exact same message, or a better one, with one image. And at the end of the day, data science is no good if nobody else can understand what you are doing.
Lots of personal development and lots of learning both in and out of the office this summer. Three months in a new country, new people, and all new experiences. Definitely worth it, and I’d do it again in a heartbeat.