Telecom and BFSI- A better career target for data scientists

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To all the data scientists out there…Wonderful timing is now!!

This year 2020 has brought many unexpected changes in the pattern of business around the world making it move more and more into the world of digitization. Thus, all the companies around the world are it any business are ready in adopting the data cultured setup in their organizations. With more data, they can make decisions accurately and suitably for the current world scenario but this would also mean that with more data at hands there would a need for more processing to be done resulting in the hiring of a very high count of data scientists. This hiring at a mass scale would mean more valuable data insights are being brought into the organization giving great use to it.

The industry of big data is expected to have total job openings up to 4,165,519 by 2023 from 2,348,620 in 2019.

To be precise, the sectors telecommunications, BFSI, manufacturing, and healthcare are the topmost sectors alluring more data scientists. Telecommunications and IT are having the largest big data market having about 33%, BFSI with 14% market share, followed by health care growth at 9.6% market share, says the experts.

Therefore all the data scientists out there must focus on the areas they need to be well expertise on and to great giant wise steps in order for them to get in a great job/career opportunities, as the need for data scientists is growing rapidly as the markets of all sectors mentioned above and others are growing. In the telecom industry, by using large data sets they are escalating their 5G operations in order to detect fraudulent call patterns. In financial sectors and banking statistical evaluation is required by data as depicting the credit fault rate is important in banks and related sectors. And in health care pharmaceutical data science could pave the wave for manual errorless operation and it could assist diagnosis of complicated diseases like cancer depiction also in biosciences.

As for the conclusion, all the sprouting data scientists must take active steps in learning about the environment and moulding themselves according to it by being aware of the now growing fields.

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