There is undoubtedly an increase in the demand for data scientists so we thought we would take a look at the factors that are affecting the demand and also those factors impacting upon the lack of suitable candidates.
Not only have companies been using data science to handle their own data pre-Covid-19, but during the pandemic they have scaled up their data usage to measure the effects of the pandemic on their businesses in order to find solutions to newly-emerging problems.
The explosion within the sheer amount and complexity of data that each and every person produces thanks to our interactions with technology, has led to an urgent need for companies to mine, clean, sort and model that information in order to make sense of it in relation to their business.
The actual global value of data science has increased from around $4bn in 2019 to $64bn in 2021, which goes some way to demonstrate why everyone is requiring data scientists, and that is not counting other disciplines such as data analytics.
Before the pandemic, the role of data scientist was still very much in demand, being considered cool and displaying huge growth. The reason behind the heralding of data science to such a crazy height back then is possibly down to the fact that there is much overlap and misunderstanding between data science and the other newly emerging roles. When a hiring manager does not understand the differences between these seemingly similar roles, the job specs and hiring can draw in candidates who are then given more responsibilities, some of which are outside their skillset. A lot of the time the candidates just get on with it, tired of having to explain themselves and their role to management who are not listening. This can ultimately lead to projects falling behind because certain roles are stretching the data scientists or because there is just too much work to do in the allotted time. If ‘data scientist’ is considered a one-size-fits-all title, then of course when polls are done, it will seem that the only jobs in that realm are those of ‘data scientist’.
With the ramping up of data projects, the market for data scientist roles has bounced back from a lull during 2020 due to the pandemic and lockdowns affecting the economy. There was, even then, a demand for data scientists, even if the job boards didn’t reflect this, and there is even more of a demand now for those skilled individuals.
And there is no sign of a slowdown. Data is expected to be worth $103bn by 2027 and that is without taking into account those sectors connected to it either, which could lead to an increase of jobs of over 15 percent within the USA alone, probably mirrored globally.
With advances in technology, human beings’ data creation becomes more complex and increases constantly. As it improves, more businesses use and harness its uses. Something like the Cloud, which did not exist in its present form a decade ago, is becoming integral in how companies handle their computing, storage and data, and with this comes the need for more workers who can handle and control it.
A major factor in an even more increased demand is that firms are seeking to improve efficiency and use their data to grow their business beyond their traditional model. There has been an increase of data science courses in order to fill the skills gap, which is still a huge problem for companies filling the vacant or newly created roles.
Right now, the correctly qualified and experienced candidates are hard to find because they are already in roles where they are using those skills already. Only dedicated experts and partners know where to find them. It will take a while before the shortages can be corrected and until then, you either need to know where to look or you need to know someone who does.
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