Advanced Analytics Lab

‘I got to know Nationale-Nederlanden via a friend from my Data Science Master’s at Tilburg University. She was already working at NN as a data scientist, told me that she really enjoyed it there and that there was a vacancy in her team. She asked me whether I wanted to come in for a chat.’

‘In reality, it can be disappointing to see the extent to which companies are data-driven. But NN has access to a lot of data and data scientists can use it to carry out genuinely predictive analyses. And that’s the kind of work we like doing most! It’s what really attracted me to the company.’

‘I work in the Advanced Analytics Lab, a centralised team that works for all NN business units, and I carry out assignments for NN Group’s Human Resources department. I’m currently researching the innovative opportunities that follow on from collecting anonymised data from CVs. It’s important for recruitment to look at the best fit for the job. To what extent can we predict this using machine learning technology?’

Wat I do as a Data Scientist

‘You might think that I spend the whole day behind a computer. Actually, the opposite is true. I’m involved in models from the ideas phase right up to implementation. As a result, I have a lot of responsibility and lots of different tasks, such as project and stakeholder management, which I really enjoy. On a project, I take account of all the stakeholders involved, who each have their own interests and expectations. As a data scientist, you also have to know when you’re heading towards the so-called ‘danger zone’. We always stay away from that. For example, does the law allow us to use data, taking account of GDPR? And what do we want ethically? I also have an educational role: I try and explain to colleagues as best I can what data science is and how you can use it to help us achieve our corporate goals.’

‘So, at NN, we use data every day. Of course, we’ve got enough challenges. Nationale-Nederlanden has a long history and is made up of various businesses. As a result, lots of different data has been collected, which hasn’t always been obtained and entered consistently of course. Fortunately, we have a data quality team that focuses on this. Because data quality is crucial for data scientists to deliver reliable models.’

‘I start my working day at around eight in the morning. It’s fairly quiet here at that time, so I can focus on my analyses. I also have regular meetings with my project stakeholders. As a team, we hold a demo every two weeks, which is an opportunity to show one another what models we have built. We also have a morning stand-up meeting several times a week. This means that we are properly up-to-date with what we’re all doing and can help each other if necessary.’

A range of different specialists

‘My team is full of data scientists, but we each have our own specialist area. For example, I really enjoy finding out what the business wants and how we can apply our technology to improve how people work. Whereas another colleague enjoys focussing on the technical implementation of models. The range of different specialist areas contributes to a great team spirit and atmosphere. We help each other a lot. Everybody wants to contribute to the innovative nature of NN. And if you’ve got a cool idea, you’re given the space and opportunities you need to implement it. It’s so inspirational and that’s why I enjoy working at NN.’