Interview with Jorrit Peters @ Telia Company

Hi there Jorrit! 

Please tell us your name and your current title?

My name is Jorrit Peters and I am working as Data Scientist at Telia in a team of 4 data scientists.

What are you working on right now, something exciting you can share?

Inventory optimization is an interesting and clean application of optimization mathematics where we strive to optimize the storage of products, shipment, the shops and the central warehouse. Our business reality can be converted to mathematical constraints.

How did you get where you are?

By always being interested in mathematics and programming and choosing the right study programs. I completed a bachelor of Econometrics in the Netherlands while working part-time as a Data Analyst. After this I moved to Sweden to study the master of Applied Mathematics at KTH. But I would say an interest in mathematics, programming and data is the main reason how I got where I am.

What are the most interesting aspects of your current job?

The variety of different projects and the immense improvements one gets with properly executed and implemented algorithms. Working in large companies has the advantage that there are many different parts where one can act as an internal consultant, analyse the processes and then apply interesting algorithms. The iterative process of understanding the business, doing the mathematics and explaining the solution is what I enjoy most in my current work. 

Is there anything you would have liked to know about being a Data Scientist before starting a career in this sector?

The data is never as perfect as you would want it, or like it is at the university. The fact that the data preparation and business understanding phases have such a great impact on the success of the project is something I did not expect. One can create the most impressive model in the whole world and still not create any business value, if you don't get that right.

What technologies do you believe will become the next ”big thing”, both in the short term and the long term?

In the last few years there has been a lot of interesting work within Deep Learning and right now many new platforms are being built for the optimization of distributed work needed for large scale deep learning. Hops (http://www.hops.io/) is a good example of one of those new platforms currently being developed (in Stockholm!). The next big thing for most companies would be to actually implement deep learning in many different parts of the organization and the world. Making the step from impressive model performance to impressive implementation and business value.

Lastly, do you have any interesting books in our sector to recommend for summer reading?

This summer I will read Deep Learning with Python by Francois Chollet. He has written the python library Keras which is widely used at many companies and in academia. The book looks really interesting and useful!

Thank you so much for participating and sharing your tips and ideas! Have a great summer.