Life as a Data Scientist Meet the team!

4 min.
16 January 2019

”Data science is hot! Changing your job title to data scientist on LinkedIn will trigger a small army of recruiters to swarm you with all kinds of awesome job offers. So in terms of career prospective jumping on the data science hype train seems like a good bet. But what skills do you need in order to be a good data scientist? No wait, let’s rephrase that question: what is data science in the first place?

This might seem like a silly question but if we dig a little deeper we find that data science actually does not always mean the same thing. If you ask different people it can be anything from market research to hardcore artificial intelligence. Although both of these extremes build on utilizing data, the skills needed for either discipline vary wildly.

So what does data science mean in the context of This series of blog posts is meant to shed some light on what we, the data scientists of, think data science is and what a good data scientist should be able to do. We have identified four key aspects that should be central in the skillset of every data scientist and asked some of our team members how these aspects feature in their day-to-day work.


The people

Before we start our series of blogs for real we want to give you some idea of who these people are that work in the Data Science team at How did they end up at How did they end up working in Data Science? What do they like to do when they are not doing the science? You’ll see we are a pretty diverse bunch!

Loïs Mooiman

I started at as an intern for my master thesis in June 2017. This was before the Data Science department was created and I became part of the Search IT team. All the other Data Scientists were scattered all over the company. When I finished my studies, wanted to start a Data Science department and I liked so much that I stayed. So, officially I started working here in February but I already was a part of the company for some time.

When I think about Data Science, I feel it is a very broad term and practice. My personal view relates a lot to Artificial Intelligence, which is somewhat loosely related to the fact that I studied AI for 5 years. 😉

Applying the mindset and method of learning from your data in a systematic/mathematical way and keep on learning from it by incorporating that into the algorithm, that is Data Science for me.

Currently is still at the beginning with integrating Data Science and in some aspects it is not even ready for integrating it. Thus, the future will be very interesting and hopefully Data Science will let serve their customers, partners and its own employees even better.

”Every day the algorithms will learn and every day we will learn from them.”

Asparuh Hristov

I started my journey at in mid 2018. I have two (similar) passions 1) solving puzzles, finding patterns and optimizing pretty much everything, and 2) rock climbing. The first one took me first to Germany and then to Amsterdam. Before finding the best combination of challenging and impactful work at, I wandered for 2 years in the world of optimizing online bidding algorithms and 4 years in a PhD reducing the processing times of bank transactions. The second passion took me to places like South Africa, Greece, Spain, Portugal, Iceland and not the Netherlands….


For me Data Science is an aggregation of knowledge and methods that uncover patterns in the data in a scalable automated process in order to add business value. The potential of this is recognized more and more both externally and internally within I believe that this will ensure more investment in Data Science, which will result in an even higher ROI. A very important side effect will be incorporating the Data Science way of working and way of thinking in any department and position within

”This means experimenting, failing, learning and improving on a daily basis.”

Wesley Verheul

As an intern during my studies in Organizational Science I got acquainted with advanced Excel in a business setting. Ever since I felt that a data driven approach to improving organizations was my call. A journey from Excel to relational databases, programming, distributed processing and statistics commenced, and after a trip around the world I ended up at in October 2016.


”To me, Data Science, as a combined skill of programming, statistics, domain expertise, is nothing more than a means to create and prove customer value. The faster and easier we can do that, the better.”

Although statistics and computers have been around for some time, the rapid increase of data and computing power has made Data Science come truly alive only just now. This means we are at the start of what is all to come. For I envision Data Science to become an integral component of every aspect of our company, whether it is commerce, customer service, HR, logistics or any other domain.

At we have the motto ‘every day better’. This is usually considered synonymous to innovation – launching new products to improve our customer experience. From this perspective, I consider hypothesizing, modelling, experimentation and learning from customer feedback (read: data) as the most crucial phases a ‘cheap idea’ has to go through in order to materialize in a new product. However, innovating is one thing, maintaining and scaling a product is a whole different ballpark that is often overlooked. Due to the immense growth of in terms of customers, visitors and sales our applications and operations need to handle increasing loads every day. Making that happen with a bunch of great colleagues is ‘every day better at’ to me as well.

Ernst Kuiper

So I am a bit of a stereotypical geek. I like board games and video games, anime, all things pop culture and science. Originally, I have an academic background in astronomy. In terms of subject matter and way of working that seems pretty far removed from online retail. However, since leaving academia I have learned that knowing how to handle and understand data is a quality that is becoming more and more important to have. And that is one thing that both astronomy and have in common: data is invaluable. So starting from ‘just working with data’ I kind of stumbled into becoming a data scientist.

I have been doing data related work since before Data Science became the big thing that it is now and to me it is the culmination of a variety of different disciplines. Handling, processing and understanding data, generating and communicating insights, using these insights to make valuable and scalable models and actually implementing these are all essential skills within Data Science. And personally, I feel there is great synergy between them. In isolation they can already be powerful but putting them together is what really makes an impact.

Data Science at is still relatively young. That is exciting, because that means there are plenty of problems to tackle. It also means a lot of change. I started at about 1.5 years ago when the data science team was still very small. If I look at the team now it is about ten times larger than when I started and the way we work has evolved significantly. But maybe what is most exciting is that we are making a positive impact on the company and our customers. And we are just getting started.

”Everything we learn today, we can use to improve things tomorrow. For ourselves, the team,, but most importantly the customers.”


Joep Janssen

I studied Operations Research and in my spare time I like to be busy with food, both when it comes to eating and preparing it. Because of this I also have to ride my racing bike every now and then.

Data Science is a fascinating field to work in.

”The combination of making sense of data by performing ‘desk chair archaeology’, building a picture of what is actually going on within a population of customers/products and deriving value from those insights is what makes Data Science fun.”


When I look at and the role of Data Science there I think it will become an integral part of every process within For everybody involved this implicates a more experimental way of improving our service for our partners and consumers. And deepening our knowledge of our customers and processes will lead to making shopping at better in a lot of ways: easier, greener, more personal, etc.”

Curious about the topic of our next blog? Stay tuned!