Hi, nice to meet you! Tell me about yourself.
Hi, I’m Zooey. I’m a data and tech trainee at DNB. I studied Econometrics at the UvA, both bachelor’s and master’s, which I finished last summer. This January, I started as a Data & Tech trainee at DNB.
Why did you pick this traineeship?
Well, I always found DNB very interesting because of its social interest. DNB has an exciting position in the economy and there’s a lot of data to work with. They have two kinds of traineeships, one is more focused on the main tasks of the DNB. I could also apply there, but then I found out that they have a Data & Tech traineeship, which focuses on well, the data and technology within DNB. I chose this traineeship because of my affinity for data.
What’s the traineeship like?
There are three placements of eight months, so the traineeship is 2 years in total. The themes are data, development and security. On top of that, there’s also a lot of personal growth and development, which I find very important. Currently, I’m placed at the Data Science Hub, where I’m very happy because data science is in my comfort zone. Then for the next placement, there will be a list of options, so I will get to choose. There’s also a possibility to just talk with people from different departments and create your own placement, assuming it’s possible in their team and the mentors agree it makes sense.
How did the first few weeks of your traineeship go?
The first week was onboarding so we went to the office for two days. I met the other trainees and was introduced to all the departments, where we also met all our mentors and buddies. The first week was really just to get used to the company and get to know everybody. Then you go to your first placement. I got a whole checklist to go over and met the team. Then I got to know how the computer works and everything on there. There’s a lot of compliance stuff to learn. After that, you just get to work. What I like about the traineeship is that there’s a lot of focus on your personal development and there is a coach that helps you with this. On the other hand, there’s also training to develop your skills, which you can choose yourself and find out what you want to learn. At the moment, I’m learning Azure fundamentals, which I need for the technical part of data science. For my next placement, I’ll have to do more learning. Data science is not that far from econometrics but security and development are knowledge areas that I don’t know much about, so I’ll have to get into the books.
What does the Data Science Hub at DNB do?
There are three main areas, the first are data science projects within the DNB. This is similar to a consultancy, but they don’t just deliver the result, they take the client with them so they get a good feeling about the process. The second area is building a community within the DNB, so people share their knowledge about data science and about the data itself. DNB is very broad, there are around 17 divisions and each division has multiple departments. There’s a lot of data going around and people do a lot of different research, but we need to create a community where we share the things that are going on and learn from each other. We do this by giving open-source lectures and workshops, there’s also an open-source expert group. The last task we do is making sure the new data science platform is user friendly and has everything a user needs.
What kind of data science projects are there at the Data Science Hub?
The Data Science Hub has a lot of projects, but one I find really interesting is Know Your Customer. Banks have to assign a risk classification to all of their clients. The aim of the project is to find fraudulent customers within the client database that they might not see as risky. We created a machine learning technique and dashboard to find those customers. This makes it easier to supervise because the model selects the risky customers from the data for you.
Another big and interesting project is Dataloop. Dataloop is a tool that provides a shared overview of all data observations and quality problems. The aim of Dataloop is to improve data quality by creating a feedback loop between multiple parties within DNB. Here, you will be able to see who uses what and what the outputs are. Everyone can be up to date with what’s going on with the data. Currently, a lot of people use the same data but you don’t know what they are doing with it. This platform creates one ‘loop’ where you can see what’s going on. Currently, DNB is busy expanding the project and also implement machine learning techniques into the feedback loop.
Any final remarks about DNB?
DNB is a very unique company. If you, like me, find social impact important, it’s definitely a great place to start. Particularly for econometrics students, the data they have and the research they do is so cool, you won’t find anything like this in the Netherlands (of course, other countries also have central banks). You will certainly find a place here that is suitable for you because it’s such a big company with all these different kinds of teams within. If you’re not sure what kind of job you want, I would certainly recommend the traineeship because it’s just an extension of your studies: you learn a lot and in different places. It’s a nice way to find the perfect job for you.