First, I wanted to be an inventor, but when someone told me this isn’t a profession, I switched to architect. I’m not sure why, because my drawings were and are awful, but I guess I liked building houses in The Sims, Sim City, Civilization and those kinds of games. During my time at IBM, I found out there are still “master inventors”, but that’s probably a bit too researchish for me anyway.
I’m a Machine Learning Engineer, or Data Scientist, at Schuberg Philis. A Data Scientist can mean many different things to different people, but for me it’s solving business problems with data and machine learning solutions. I guess that’s still a bit vague. So: currently, with a team of more than 20 people, I’m building a data platform to gather data from machines in over 100 breweries all over the world. With this data, we build applications that support operators in the brewery to improve the efficiency and quality of their work, for example by providing insights into when and why certain stops occur on machines.
A friend, who I knew from my previous job, moved to Schuberg Philis. He was super enthusiastic, and he told me about the cool stuff and smart people he was working with. So, he asked me to come by for an informal talk. Talking to these people and seeing how they build innovative solutions that work for dozens of breweries all over the world, really got me interested in the place. After that talk I had 3 interviews and got hired.
Luckily for me, I got the job before the crisis, but started from home on 1 May, all virtually. I can’t really complain about how it went, because everything was super well-organised. My laptop, phone and even a welcome lunch were all delivered to my home. What I probably miss the most is the informal communication, which you usually have during lunch and coffee breaks. What did help me to compensate for this, was planning a lot of virtual one-on-one meetings with everybody from my team and people within Schuberg Philis.
That’s a difficult one. I think it’s the fact that I’ve always been able to see and learn a lot from different customers and industries. It’s always a nice moment, after you tried to understand their work and data, to show a customer something they didn’t know yet and how that can help their day-to-day work.
Additionally, I can work with people who are very good at what they do. Recently I watched a demo of our ‘gamification expert’, who built a virtual 3D model of a brewery packaging line in virtual reality – so I asked him to show me how to build this by myself in some gaming engine.
I think that’s making sure to work effectively with so many different people and disciplines. For example, in the morning I have a conversation with someone who’s building the infrastructure (physical hardware, sensors and cloud services) on how the data is processed before it comes to me. Later, in the afternoon, I talk to an end user who doesn’t care about that, but only wants to know how they can best use the insights from a visualisation we provide.
I don’t know exactly, but I definitely know it helps me every day. For example, in building a predictive model for machine errors, I do use and think of the mathematical foundation I’ve been taught in my algebra and econometrics courses. Or how to transform a real-life problem into a solvable data problem, like: What is the optimal schedule for producing beers of several brands?
Most importantly, I think it is the academic way of tackling a problem. Try to understand the problem, define it, test hypotheses and build a solution. All the business acumen and how to effectively communicate is something you’ll learn on the job.
Don’t try to prepare too much for your working life or a business job, but use your time to explore and dive deep into an academic problem. Companies are looking for people who have an academic level of thinking and get enthusiastic while talking about their discipline.
You can’t know everything yet, so being eager and knowing how to learn might be a good start. And to end with a cliché that I really believe in: find and do something that gives you energy!
We thank Dolf for taking the time to do this interview, and for the glimpse he gave us into his industry.
If you have any questions, you can reach Dolf on his LinkedIn page. He’ll answer your questions gladly.
We hope this month’s alumnus was an inspiration. What kind of Economics and Business career would you like to know more about? Let us know, and we will try to arrange an interview with alumni who have experience in that field for a future instalment of Alumni in the Spotlight!