Data Science: the sexiest field in IT
The Harvard Business Review dubbed data science “the sexiest job of the 21st century”. In the beginning of 2018 TMC opened up a new data science cell for its Eindhoven headquarters. Currently about twenty Employeneurs have joined the new cell. We asked the head of the data science cell Bram Thelen and data science Employeneur Ignacio Vazquez to tell us more.
Data Science and its tremendous potential
‘Data is one of the key drivers of innovation today,’ says Bram Thelen, head of the data science cell at TMC. ‘Concepts like artificial intelligence, Big Data and smart manufacturing are new disciplines with tremendous potential that all depend on data. They play a big part in shaping our future.’ Many companies are eager to develop the skills and knowledge to analyse their data flows, Thelen says, but they often don’t know where to start. ‘Our Employeneurs help these companies take practical steps to realise these goals.’
One of these Employeneurs is Ignacio Vazquez. The Mexican born engineer joined the data science cell from the very beginning. In his first data science project he worked with an advanced engineering group at DAF that looked at the future design of trucks. Ignacio was tasked with finding and combining data that would provide the best design scenario’s. ‘In large companies data is spread all over,’ says Ignacio. ‘So I had to integrate sales information from the marketing department with data from product development about the technology content of the trucks.’
'They play a big part in shaping our future.’
After visualising these data in a graph, Ignacio provided the engineering group with the tools to ex-trapolate future scenario’s for different technology choices. ‘My graph was something the engineers could play around with. They could tweak sales data or technology parameters and see the results graphically. The job of the data scientist is coming up with ways to give stakeholders the best in-sight with the available data.’
TMC’s data science cell supported Ignacio to transition from being a purely mechatronics engineer to a full fledged data science specialist. Having other Employeneurs in the new cell who were also taking their first steps on the data science path was a great help, he says. ‘When you enter a com-pletely new field like data science, you are uncertain about whether you are smart enough to under-stand the problems. When I talked to the other Employeneurs I realised that everybody worried about that. That gave me the confidence that I was not the only one trying to puzzle out those ques-tions.’
Hiring or becoming a Data Scientist
In cooperation with KIVI Ignacio recently organised and hosted a pizza session at TMC where two experts presented their practical working experiences as data scientists for a group of high-tech en-gineers and managers. The response was enthusiastic, yet Ignacio also warns against too high expec-tations about data science. ‘My colleague talked about her experience as a data scientist in a scale-up company. The scale-up thought she was going to generate all these predictive data models, and that sales were going to skyrocket because of it. But it’s not that easy. First you need proper data infrastructure, like a lot of code and ways to transport the data efficiently. The time from a business question to a data answer takes much longer if you don’t have that infrastructure yet.’
When should a company think about hiring a data scientist? According to Ignacio it’s when the company is both data intensive and has good business questions that can be answered using data. ‘If you start playing around with data, but you don’t know what you want to find, then nothing will come out of it. But if the things a company want to learn can actually be answered with data, then a data scientist can be of great help.’
'You have to stay constantly up-to-date because what is new today is old tomorrow.’
Becoming a data scientist requires an elaborate skillset. You need to be able to write code, under-stand statistics and have enough domain knowledge of the field you’re working in. On top of that you need to be able to communicate with different departments to get hold of the right data and to explain your data models to the stakeholders you work with.
According to Bram Thelen the most important quality a data scientist needs is curiosity. ‘You have to be able to come up with surprising ideas and concepts to link different data sets. You also have to be open to what other people are doing and how you can improve on that. And since the field is still developing, you have to stay constantly up-to-date because what is new today is old tomorrow.’