Data Scientist, Stijn

The first beginnings of Crowdscan go way back, to my PhD project and even before. People, by their physical presence, cause attenuations in radio signals. The more people, the stronger the attenuation. This is the basis of our solution to ‘scan the crowd’.

    During a live experiment at Tomorrowland, we saw that our counts nicely followed the graphs of other more time-consuming and labour-intensive counting methods. This is the moment we realised that we needed to do something with this technique. Crowdscan was born.

    I’m responsible for the data analysis. I work on the technique itself, searching the sensor-data for interesting insights, and I lay the foundation for the features we offer to our customers. It’s important to go deep into the data, but also to zoom out and to validate your findings with reality.

    Radio frequencies are a complex matter. A lot of things, other than people, can cause attenuation. We need to filter out all disturbers, to make sure the data tell us a true story. Each new project starts with a calibration when the area is empty. We acknowledge the numbers with other counting methods and we systematically match our findings with the context of that specific area.

    Communication and collaboration are extremely important in this role. When you’re working on a feature for weeks, you need to talk with the colleagues about what you’re doing. This forces you to document and structure your research, and they often give you new insights on how to tackle the challenge. Additionally, clear communication outside of the Crowdscan team with other strategic partners is highly important as well, particularly in the context of joint research projects.

    I think our future colleague will have at least a basic level of experience in data science. But as the job requires a lot of self-study, it might also be interesting to find people with a totally different background and perspective. To be creative with data and technology, I think that’s the basis.



        To work together, with a motivated team

        To find different angles to tackle a problem

        To expect the unexpected


        To be curious

        To be creative

        Infinite learning


        To hold on to a fixed pattern

        To give up quickly

        Lack of communication

        Data scientist stijn

        Next steps?

        So, how long does it take until I got the job?

          1. Quick coffee

          2. First interview

          3. Second coffee with management

          4. You got the job!


          Vestinglaan 44 2640 Mortsel Belgium
          BE 0748810801