Why are mathematicians and statisticians becoming the darling of the industry

Computers have revolutionized the world of business a long time ago, and it is doing more of that in the last decade. With the advancement of computing techniques and storage mechanism, businesses are able to collect and process extremely large quantities of data.

However, the processing of this astronomical volume of data and the generation of actionable intelligence and insights doesn’t take place by itself. Rather, it has to be acted upon by human beings who are knowledgeable and has the required skills to derive the insights.

Welcome to the age of big data – an era where mathematicians and statisticians are regaining their lost sheen and are getting placed in the same bracket as that of computer scientists. In fact, the line between the three specializations are disappearing fast and the three otherwise distinct professions have merged together to give rise to a new breed of professionals called data scientists. Their job is referred by many eminent personalities of the industry as the sexiest job of the century!

To understand what they essentially do, let us be very clear that mathematics is the basis of the other two disciplines. In statistics, mathematical tools and techniques are refined to meet the needs of dealing with large quantities of data. In computer science, mathematics finds its application in constructing and illustrating the theoretical models of programs and information processing mechanisms.

However, as one specializes in any of the three distinct domains, the same basics gets proliferated into detailed application oriented tools. For becoming a data scientist, one has to be extremely skilled in mathematics. That is taken for granted. Apart from that, one has to be skilled or at least have working knowledge in any one of the other two specializations.

The profession is demanding, but also highly rewarding. One can build an exceptionally good and satisfying career by becoming a data scientist. In fact, for them sky is the limit. But a lot has to be done before one can actually be called a decent data scientist.

To start with, a Ph. D in one of the specializations is a must. There are some who becomes a data scientist after having experience of as long as 10 years or more in one of the relevant disciplines. Apart from that, one has to extremely tech savvy and have the aptitude for asking the right questions.

There are some fancy topics like machine learning and artificial intelligence that has captured the imagination of the public. But it is not easy to reach that level of proficiency so that one can actually work on those areas.

If anyone is interested in knowing more details along these lines, he can see my blog articles or may contact me to get a professional consulting.

Author’s Bio:

The above article is written by the author Worris Levine and the output of his research show a new way for the revaluation of information technology and computer era.

The author of this article, named Jeo Nash, has studied in detail the requirements of a good web design company, and concluded the fact that an economic web design company is the need of the hour.