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Constant learning is key to a successful data science career

Graduates today need to be aware that the speed of technological change is such that they will need to learn new skills and take additional courses throughout their career, if they are to remain relevant.

The rise of the fourth industrial revolution (4IR) means that today, technology and analytics are seeping into industries across the board. Furthermore, it has led to the rapid growth of what were previously relatively niche fields, like that of data science.

According to Melissa Jantjies, a systems engineer at SAS, data science could be described as a greenfields sector, in that it is relatively new and thus has none of the attendant baggage associated with older markets. She points out that owing to the manner in which it has exploded in terms of demand, the need for data science skills is growing exponentially.

"Owing to the high demand for these skills, there's plenty of opportunity for graduates to build a successful career in this arena. However, the trick to remaining relevant, particularly with the current pace of technological change, is to continue learning throughout your career," she says.

"It is worth remembering that, while university offers a number of benefits, mostly it teaches you how to learn, as little of what is taught at these institutions is truly applicable to the working world. Therefore, it's important for youngsters entering this arena to understand that success will be determined by how willing they are to equip themselves with the skills needed to continue evolving."

She states that in her opinion, one of the first things graduates should do is inculcate a learning mindset, where they are continually trying to learn more and adapt and develop skills within their field.

"To remain relevant, one has to consistently be prepared to step outside one's comfort zone and learn something new. For example, I come from an economics background, but have taken on positions that have, for example, required me to learn code. While you may bump your head a few times with such an approach, this is often the best way to learn.

"The reality is that a successful career in data analytics can only be built on embracing new challenges, taking relevant courses to improve your skills and reading all of the literature around the subject that you can find.

"It is also worth noting that any time you do this, undertaking new courses or learning new skills, you not only make yourself more marketable, but this can also open new career paths within the organisation you are working for. Most crucially, trying new things will help you to determine exactly what you want your career to be, something you can't really decide on until you have experienced a multitude of different options," she says.

At the same time, suggests Jantjies, it is equally important for the organisation to provide encouragement to graduates around their education, learning and broadening of their horizons.

"Of course, it goes without saying that any graduate choosing to further develop their skills should ensure that those they choose to improve are ones that are expected of data scientists. Furthermore, focus particularly on expertise that is in high demand, as this will serve to make you more marketable both locally and internationally.

"Remember that as the 4IR continues to impact on the world, things are going to change faster and faster, meaning that flexibility and the ability to be agile in terms of learning new things is going to be more critical than ever. A final word of advice to graduates is to understand that your degree simply opens up the door to your career; you need to realise that you are not limited to any one path and must be open-minded about your future. Remember, too, that data science is a field that is large enough for you to move in a number of different directions, and what you choose to learn while in the workplace may ultimately lead you onto an entirely new career path," she concludes.

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