One of the driving factors that is increasing demand for data scientists is the growing power to collect data from the physical world. We can see this in a wide range of areas that digitization had not penetrated before.
“In the field of manufacturing we see quite some trends in Industrial IoT (IIot). Just like its ‘normal’ counterpart, this is all about connecting industrial devices, ranging from large-scale production equipment to things like collaborative robots (Cobots), Automated Guided Vehicles (AGV’s) but also energy monitoring solutions to allow for more efficient energy usage,” says Bas Tijsma, Senior Engineer and Manufacturing IT expert at Philips.
Tijsma adds that the trend of connecting and digitizing industrial environments will grow with the advent and expansion of 5G networks, which can provide robust connectivity in factory floors. “5G is also helpful for bringing information back to the operators and supporting engineers; data that they could only access from their office PC can now be easily streamed to the shop floor (or home),” he says.
We can see similar trends in many domains. In health care, for instance, from personal gear to hospital equipment, there’s more connectivity and data-collection capability than ever before, which creates unprecedented opportunities for applications of data science. “The evolution in health care technology in robotics, genomics, medical devices, IoTs, fitness wearables in the last decade plays a key role in the growing demand for data scientists,” says Priyaranjan Dhar, Talent Intelligence Data Scientist at Philips.
Another example is the insurance industry, where service providers can use IoT technology such as telematics devices in cars and smart home sensors to better assess risks and provide personalized premiums to clients. There are now many startups that are leveraging data science, machine learning, and IoT to provide insurance services in previously uncovered areas. But we’re also seeing a shift in established insurance companies such as Lloyd’s, which is engaged in its own data science initiatives and is also helping nurture the fledgling insurtech space.
Brick-and-mortar retail is another are that has had to adapt to the age of digitization and artificial intelligence. One of the great examples is Walmart, which is now fast busy acquiring data scientist and AI talent to keep up with Amazon, Alibaba, and other companies that started out as e-commerce platforms but have become hi-tech omnipresent retailers. Meanwhile, retailers that failed to adapt have had to cede their position to tech-oriented upstarts. The most prominent example is Sears, which filed for bankruptcy in 2018 after more than a century of operation.
There are scant areas that have not been impacted by data science. “Data science is already playing a crucial role in all the areas one can think of. Wearables have helped save lives by constantly tracking vital signs and signaling if there are any anomalies. IoT, smart sensors, 5G have found applications in self-driving vehicles and in fully automating the retail purchase experiences (Amazon Go stores),” says Karthik AV, Senior Manager and Data Scientist at Philips.
At big tech companies where the technical infrastructure is in place, data scientists will find the opportunity to put this vast store of data to good use and turn it into actionable insights. When starting work at Philips, Tijsma, who has a background in mechanical and industrial engineering, was amazed at the sheer amount of IT systems that was at his disposal, and he quickly learned to use them to improve production performance at manufacturing plants.
“I’ve always had a thing for optimizing systems so that quickly became part of my work. After having done several industrialization projects we realized we had lots of data, but only used it for troubleshooting purposes, after the event had already occurred and basically too late. This lack of predictability was essentially the start of one of the first data science teams in a manufacturing site and it is still my passion today,” he says.
“Philips has some of the most advanced production sites in the world where these technologies can be pioneered and tested,” Tijsma says. “One of the advantages is that you work with live data and you can immediately see the results of your work in action.”