Just like there happen to be various categories of statisticians like for instance biostatistician, econometricians, and operations research specialists and so on, there are also categories of data scientists. In any particular industry, when it comes to one discipline, there still happen to be multiple people acting and working in similar yet different fashion. A simpler example would be the various categories of business analysts. These could range from professionals who have an expertise in the field of marketing, or product or ever finance. Similar is the case with the field of Data Science. Did you know that many data scientists, don’t even happen to have the same title that of a data scientist?
Now let us begin with the various categories of data scientists that are here, thriving and functioning in the industry. Firstly there are those who have statistics as their strong suit. They happen to be involved in development of new and improved statistical theories for the development of data science. They have a proper expertise in various subjects such as statistical modelling, experimental design, and sampling, clustering, data reduction and so on.
Then there are those data scientists who have maths as their strongest suit possible. These people are usually the ones employed in high tech governmental and non-governmental agencies like the national security agency, the operations and research departments and sometimes they are even astronomers or people working for the military and defence services of a particular country. These are the creamiest of the creamy layer of the society and are usually found to be collecting, analysing and extracting value out of data.
Those professionals who are supposed to be having expertise in the field of data engineering are known to be fitting right in into the third category of data scientists. These professionals generally work with a number of data analytical tools like Hadoop as well as work with database or file system optimization or the newest hot word in the market, are involved in the process of data plumbing.
The next few categories are although not as big hits as the three that precede them, but at the same time are extremely important as well. For instance, those who are involved in the field of machine learning, happen to be extremely strong with algorithms and computational complexity, which happen to be their areas of work influence.
Those professionals who work in the business category are usually those who work in optimization as a part of the various decision sciences. Their functions were apparently carried out by various business analysts earlier in the big gun type of companies. Whereas those who usually work with code development are found to be working in the field of software engineering. Then there are those data scientists who fall in the category of data visualization, spatial data and many more.
For a data scientist or a data aspirant to actually fall in any of the three categories, it is very important for them to first develop their faculties. For which most of these aspirants usually join professional training institutes like Imarticus Learning.