Data Science Working Student (m/f)


We are looking for a working student in Data Science to reinforce our machine learning team at - a restaurant assistance and AI solution based in Berlin, Germany. 

You should be a major in data science or of related studies. Some prior work experience is of advantage. You should love designing machine learning models and algorithms. You should be familiar with Weka, TensorFlow, Amazon, Google and Apache Machine Learning-tools. 

You will support our machine learning and software development team. Therefore you must be willing to be creative but thorough, pragmatic but  create beautiful calculations fast and error free. 

We are happy to support any master/diploma project. In any way, your will add the design of some outstanding digital products on your CV.

You should be able to work in our Berlin office in Germany. Working languages are German and English. All concepts, tickets, meetings, and coding are done in English of course, most legal documents are bi-lingual.

As we genuinely care about fair and enjoyable work conditions and a better world for everybody and every species we signed the to express our attitude, it is important to us that you share our spirit. More over we have very agreeable policies for work from home flexibility and a very flexible work schedule (core working time, trusted working time). 

We are an open-minded, women- and parent-friendly, international team with an up-and-coming product, rock-solid financing, a worldwide client base, located in the heart of the European digital epicenter.

Start anytime. 

International candidates must have a valid working permit or qualify for the EU Blue Card or study at a European university.

We heartily welcome you to Berlin and Seatris.

Martina Schlager, COO Seatris GmbH

Applications to


Should You Apply?

Absolutely! If you don't think you meet all the recommended requirements, that's okay! As long as you are excited about Seatris, JavaScript, ROR, AWS,  the web, or marketing, we can find an opportunity for you.

Please include a link to your LinkedIn Page, public GitHub or repo of choice.