Attracting Top Data Science Talent

Purple is the new black

In the world of data science consultancy firms, Pipple is one notable mention. With a focus on using creativity and mathematics, they solve data analytics problems in a various range of industries. In May, me and Roy had a chance to talk to the two lead data scientists behind Pipple: Jeroen de Haas, a self-described 40 year-old man with grey hair and Thijs Verhaegh, his younger counterpart.

Background

If you think about a data scientist you don’t think about a 40 year old man with grey hair, you think about a young man with a beard who’s 26 now but his age was estimated as 36..

Jeroen started out as an actuarial analyst in 2002 at Interpolis (part of Achmea) after having graduated with a degree in Econometrics. In this position, he built statistical models based on millions of historical car damage claims. For example, he looked at the variables that can predict car damage claims, such as the zip-code of clients.

After these mathematical roles, Jeroen eventually took up more commercial roles, followed by management roles. From the moment he started, the banking world went sky high until the financial crisis in 2008/2009. That made him realize that the banking world was shrinking. Firing employees was ordinary practice, everyone was reorganizing their company — “you didn’t work in an organisation but rather in a reorganization because of the constant changes.”

As continuing to work in banking until someone decides to let you go was not an ideal perspective — Jeroen asked himself the question: is this the most exciting place to be at this moment in time? Wanting to have a fresh start, Jeroen remembers thinking: “If I could pick any job in the world what would be my ideal job?”. He adds: “Now I have more than 15 years of experience, but when I started I had no idea, because I never went to in-house days. In 2015 I really took the time to answer this question”.

The answer turned out to be Pipple, the data science consultancy firm for large and medium enterprises. At Pipple, the main focus is finance and logistics.


Econometrics VS Data Science

Although we can’t know what the ideal job for Jeroen would have been back in 2009, we do know about his ideal study program: “If I could choose between studying data science and econometrics, I would choose for philosophy, because it goes in depth about the really important questions.”

Jeroen further describes his desire to get to the bottom of things, not through philosophy, but rather through mathematics: “What I really like about the field of Operations Research is that you can prove everything. For example, you often see that products sold by webshops are shipped in boxes with a lot of empty space. Then the question could be: what is the optimal choice of packaging box sizes to minimize the total weight (given the constraints: e.g. not possible to have 10,000 different sizes of boxes). Here you can determine a theoretical lower bound and compare that with your own solution. That is what I really like. For example, in forecasting you can only make statements like: there is an X% probability that event Y will happen. As such, you restrict yourself to probabilities. In mathematics you can really prove that something is shorter or better or faster or more efficient. I’m not sure whether you always learn this skill in the field of data science.”


Business

As a data science student, one of the topics that often comes up in discussions is the ideal future working environment. Is it at a big firm that has resources and established protocols, or at a start-up? During my board year at Pattern I had the chance to catch a glimpse of both worlds, and — to be honest — the answer still remains somewhat unclear to me. That’s why I asked the Pipple founders to share their personal views on this topic.

According to Jeroen, the young generation does not necessarily want to work for the traditional corporates of today. “They are looking for challenges, variety — they want to learn, grow and discover multiple industries to widen their knowledge.” Adding with a wink he concludes: “Such corporates will therefore have a big problem attracting new top talent like Thijs.”

[The young generation] is looking for challenges, variety — they want to learn, grow and discover multiple industries to widen their knowledge

Except for the variety that keeps things interesting, Thijs and Jeroen share another benefit of working for an external consultancy firm: transferring knowledge and lessons learned from one client to another. For example, the internal knowledge they have about cluster algorithms for 3D scans can be used for multiple clients. So their clients do not need to have this specific skill set in-house, but do reap the benefits of (external) expertise.

According to Thijs, the two perspectives actually complement each other. They often work together with data analysts from the client side to introduce new tooling after their team had experienced the limitations of Excel. Efficient collaboration is therefore crucial to any project. Admittedly sharing know-how between the two parties is not always easy: “This part, figuring out what the client really wants and needs, is most challenging”, Thijs says.

Creating business impact is done by making people feel involved and getting them enthusiastic.

About the interaction with clients, Jeroen remarks: “It’s not as much about what you do, but more about how you do it.” Thijs makes sure to note that although the underlying assumption is to deliver high-quality service, creating business impact is done by making people feel involved and getting them enthusiastic. Confirming his claim, he reminisces about how in the previous week, the analytics team engaged in a 30-minutes football game after a 2-hour meeting with the clients. At Pipple they try to incorporate fun not only in meetings, but in anything else. An example of the company’s ongoing goal to change the status quo can also be seen in the way they designed their website in a non-traditional manner. As they say at Pipple: ‘why not do it differently’?


Data science is still a new field, and more and more young people are attracted to this industry. From an outsider perspective, it has been interesting to see how Pipple exploits this trend to build its tribe: Jeroen is convinced that the variety of fast-changing environments is an attraction point for fresh new talent. Affinity for doing things differently has always been a landmark for the millennials. My closing question to you is — what will make the difference to you while job hunting? Let us know in the comments!