A Day At Datacadabra: Data Scientist Marcel

Digital intelligence takes many forms: artificial intelligence, machine learning, computer vision, data science, you name it. Within Datacadabra, almost all forms are used, depending on the client's needs. For example, the MowHawk is an application to mow roadsides smarter and an example of Computer Vision using image recognition. A project with a completely different technical focus is the Luistervinq, an application to map the use of outdoor spaces, as it uses sound recognition instead of image recognition. This already shows a little more of the technical differences that exist within Datacadabra, but to get a little clearer on this, we asked Marcel Gouka a few questions.

Marcel Gouka is a Data Scientist and is mainly concerned with analyzing data and writing Machine Learning models. However, the tasks he takes on and performs are a lot broader than that. 'I also deal with designing and building the software for our applications and projects. In addition, the company is in full development and part of my time also goes into setting up technical structure, documentation and work processes.'

'Every day starts with a cold shower, half an hour of yoga, breakfast and then work. If possible, I try to do the difficult things in the morning without getting distracted and try to do the meetings and the more trivial tasks, such as documentation and administration, in the afternoon. That way I keep productivity highest. Furthermore, a typical workday always starts with a stand-up to go over tasks, schedule and any problems with the team. After that, I often dive into code for our projects or our own code base. I may also engage in literature research, data exploration or training models.'

Marcel is currently working on two projects, one is for a new client and the other is a familiar one: the MowHawk. At the moment I am working on starting a project to classify substrates in 360 degree images for a new client. I am also working on the maintenance and continued development of the MowHawk. This is running in the field for the first time and that will then require some attention to make sure the system keeps running well.

When asked what he likes best about his job, he answers with one word, "Versatility. Data is everywhere and anywhere there is data you can do something with Data Science. We have already done several projects with completely different topics. For example, we have projects with video or sound, but also with mathematical graphs. This way you keep learning a lot and the work remains challenging. In addition, solving problems using artificial intelligence remains endlessly fascinating'

Marcel goes on to say that he loves the working atmosphere at Datacadabra. 'We have a team of talented and motivated people and some great and challenging projects. It's sociable, but there is definitely hard work.'

Finally, we discuss what he is most proud of in relation to his work within Datacadabra. His answer reflects well the growth that Datacadabra is currently experiencing: 'When I joined full-time, in terms of technical structure, there wasn't much in place. Now we are six months down the road and in that time I have set up structures for the technical team. For example, we now have rules that the code must comply with, we work with a branch and pull request strategy, the MowHawk code has been redesigned so that it has become a solid product, we keep track of important decisions by means of decision records so that we can read them back later, a start has been made on the Datacadabra code base and we maintain technical documentation.'

In short, a lot has changed since Marcel started at Datacadabra. These changes and additions show well the growth Datacadabra is currently experiencing and the impact employees are making. More and more standards are emerging and the company continues to expand in terms of assignments and projects, as well as employees. A start-up that is well on its way to making a social difference through technical and digital intelligence!