A couple of years ago, IBM raised concerns with a seemingly alarming prospect for businesses relying on data science.
A report launched by the tech giant warned that roles that require skills related to machine learning, big data, and data science in general were the most challenging to recruit. Such a hurdle could become very costly, since failing to fill certain key roles in different companies could disrupt product development across industries.
Though we are within the timeframe estimated by the report, data science still enjoys a healthy state. New projections expect big data and business analytics markets to grow from its 2018 value of $169 billion to $274 billion by 2022. Growth like that can only mean that businesses still rely on increasingly requiring Python software development and other development experts.
Of course, this could mean that IBM’s gloomy projections could still become a reality, as demand keeps growing and professionals capable of filling the newly created jobs aren’t enough to cover them all. In the end, this could result in an expanded scope for data scientists, which will bring them new opportunities and possibilities as early as next year. Truth be told, 2020 promises to be the biggest year for data scientists. Let’s see why.
An increasing demand for a data-driven world
Tech experts and big data enthusiasts agree that most industries can benefit from the growing democratization of data. Accessing unstructured information is easier than ever, thanks to the popularization of social networking, the ubiquitous presence of search engines, and the numerous platforms to gather personal data. And with that large data set come a lot of useful information that can transform any business.
That’s the main reason why private companies, government agencies, institutions and organizations of all kinds are looking for programmers and Python developers. They all want to make sense out of the data they are gathering, which is only possible through data scientists skillset and specialized platforms in data management and analysis.
The trend is hotter than ever right now—and will get even hotter by 2020. IBM predicts that the demand for data scientists will soar 28% by next year, which will surely start a bidding word to get the best talent. The huge demand for professionals skilled in data, analytics, machine learning and AI will probably cause a disruption in the workforce that will have to be addressed by the education sector.
Since that pressure will be put on the market by next year, companies will have to look for creative solutions to fill the gaps. This means that the scope of current data scientists will grow, as the companies will demand more tasks and solutions from the most skilled workers in the data science field. But that also implies the development of new roles in data engineering, data governance, data privacy, and more, while also boosting other professionals (like the ones working with Python development services).
Industries that are fostering the data science revolution
The need for those new roles will be pushed by sectors that are already basing their developments in data science and by new agents that will change the landscape. One of the biggest contributors to that spike on the demand will be the healthcare industry, since new research and developments are necessarily based on the analysis of complex data to detect new opportunities related to treatments, medicines, and diagnosis.
The cybersecurity industry is also investing heavily in data science approaches to prevent attacks. New solutions are using data engineering to detect anomalies and intrusions. The method is still in development, but is already pushing the need for data scientists, data engineers, and Python development companies. In fact, this market is growing so much that its spending is expected to hit the $42 billion mark by 2020, along with its corresponding demand spike for qualified workers.
There are other industries that will contribute to this increasing demand as well. The aviation industry, for one, uses data science to optimize their pricing and routes, and will continue to require experts in the field. Agriculture is another industry that’s making a huge contribution to the demand for data scientists. This field is using data to improve farm output while also using it for forecasting and pricing fluctuations.
All of those sectors are trying to get their hands on the limited offer of data scientists available. And since 39% of the most rigorous data science positions require a degree higher than a bachelor’s degree, the whole market and the education sector in particular will be playing catch up from now on. Until there are enough highly skilled professionals for all these roles, companies will have to resort to creative solutions to fill those gaps.
That’s especially true when a new stat is brought into consideration: the fast-growing annual demand for the new data scientist roles, data developers, and data engineers will reach the 700,000 mark by 2020. The growth in scope and the new industries that are trying to capitalize on the data science trend explain this increase but also pose a question.
What happens if the current healthy state of the data science field is a bubble about to burst? What if IBM was right and the demand can’t be met by a matching offer? There aren’t clear answers right now but seeing how data science is expanding across industries, it’s unsettling to see that they can be rather problematic.