Best Industries for Data Scientists

These days with the kind of momentum that the industry of data science is growing at, it has become quite the golden time to pursue a career as a Data Scientist. It has become quite the pan-industry career, spanning various different sectors and creating multiple opportunities for professionals to derive insights through data.

Did you know that technology sector alone compromises of about 41% of the data scientists in the sector? Whereas 13% of the data scientists are seen working in the marketing sector, then 11% function in the corporate world and 9% perform consultative duties. Apart from these mainstream options, there are also data scientists working in the health care and pharmaceutical sectors, they measure up to 7%.

Now that we have fairly established what a hot and happening career data science is, let us talk about some of the best career options where a data scientist can flourish. Now it is important to keep in mind the highly valuable nature of data science and the various things that it can actually result into. Which is why we will be breaking away from the run of the mill, ordinary kind of career and shift to a little more interesting bundle of the same.

The first career in our list is the industry of Biotechnology, surprised aren’t you? But you shouldn’t really be, mainly because since the beginning of time, the field of science and medicine have been interdependent on each other. History is witness to the fact that as technology improved, almost all of the nations shifted their focus to growth and development of public health facilities.

The reason why this field will require data scientists because, as a global community we are almost on the brink of decoding the human genome and unlocking all the secrets that have remained hidden so far. For this very purpose, we would need data the size of a mountain, because it happens to be an unbelievable feat to achieve.

Energy is one other industry which is on its path to vocalize its demands for data scientists. As time passes, new potential resources of energy are developed. And in order to harness the energy output of these modern resources. Various new campaigns like the storage of crude oil, exploration of new ways to extract energy and mineral wealth from the earth and brain storming of new ways of transporting the energy sources and finding new ways to exploit solar energy and clean energy. All of these need expert data scientists to help them along the way.

Another industry which will be in need of data scientists is the quality control and source inspection industry, then the transportation industry might also mirror demands of the same. Telecommunications is one very dynamic industry that will be in need of data scientists in the near future. In order to feed this demand, droves of people have decided to take up this as their career option. Some choose the path of gainful experience during employment whereas some choose the vocational training path, with comprehensive courses offered by training institutes like Imarticus Learning.

Companies Use These Methods to Select the Best Employees in the field of Data Science

Companies, especially in the field of data science, are known to be quite the picky employers, for the very reason that there exists a lot of competition in the industry. There has been a study quite recently, the findings of which state that a number of data scientists who have been already working as professionals, learned to work the way they do not through a proper course of formal training but rather through either a professional training course or through those courses that are available online for free.

Professional training courses today, have been very much on the rise mainly because the industry has begun to actually be transformed into this quest for the most suited employee. This is because the companies today don’t just want anyone who can wing it, but rather want a professional who is able to sort out things and get the work done in the most effective manner possible. Which is why candidates are today looking to get thoroughly trained in order to become industry endorsed and are similarly looking to do professional training courses to achieve the same. In the context of India, there are quite a few professional training institutes like Imarticus Learning which are rising in popularity in terms of training candidates to be industry endorsed.

When companies look for candidates, there are few chosen tips that they all follow

  1. Firstly the companies start off with the basics and begin their search for individuals and candidates who would be proficient in computer science or have a degree in a related field. According to statistics, there are about 30% of such candidates, who are currently working as data science professionals and had been computer science undergraduates before entering the field.
  2. There are so many jobs available and so much demand that statistics state that professionals are always on the lookout for jobs, almost two hours a week sometimes. This shows that although a part of the industry there are many candidates who are willing to move on to better positions and better career roles in data science.
  1. Companies are always looking out for candidates and while doing so they ensure that they find out the right kind of candidate with the right kind of educational qualifications. While a data scientist or a data analyst would be their cup of tea, but someone who is a software engineer or a software developer would have fewer chances of getting employed by that very company.
  1. The most important trait, however, is the skillset. Many companies are extremely stringent about the same which is why candidates looking for employment have to up their game quite seriously. This is also the reason why the competition when it comes to choosing candidates also increases. Statistics state that only 4% of the employed data scientists can say quite sure that they are equipped to perform the roles expected out of them as they have the required skillset to do so.

 

Categories of Data Scientists

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.

Its the Small Data that Matters!

Big Data, surely everyone knows all that it is about, but do you know that the future revolves all around making this big data, smaller? While there may be a lot many people stating that big data is the next big thing, but those people tend to oversee the fact that everything related to big data, is entirely machine based and you would most likely require the human eye, to look at the big picture as it gradually forms. While it is no news, that the importance, evolution, analyzing and collection of everything related to big data, depends on its tools, which are commonly known as data analytics tools. These tools are basically used by Data Scientists or Data Analysts, to make smarter strategic decisions, to reduce costs, to target the right kind of audience, to optimize offerings and on the whole, in order to ensure that your business runs as efficiently as possible. Studies show that by the year 2019, the value of the data analytics industry is bound to reach about $187 billion. Its reason enough to become a part of this industry as early as you can.

Let’s start with the basics here, big data is basically a term, used to refer to the enormous amount of structured as well as raw data, which is generated by a number of businesses today. This data refers to every kind of online record of information, now that could be anything related to social media, or a machine to machine relation. The basic concept is, to be able to deal with all of this data, floating all around you in the virtual world, for which, one would need to develop certain technologies, which would help in analyzing the data, thereby resulting into various decisions that would prove beneficial to the growth and development of various companies.

In the recent times, the concept of big data has come to be the center of attention of the world of technology. There are many who believe that just storage of massive amounts of data would be able to get their work done. This is not really the case, as big amounts of data does not necessarily mean that the data would be useful. The most important point here is, how a business or a firm is able to analyze this data, while at the same time be able to draw practical conclusions from the same, in order to bettering their chances of success. Big Data being a very new concept, many companies have chosen to prioritize over the quantity of data, as opposed to the quality of it. The general idea of this field is so generic, that it becomes quite difficult for various companies to figure out which data should be analyzed, or how to conduct the analysis, or for that matter what attributes it must have. On the other hand, small data is rapidly gaining more importance, mainly because of its very specific attributes, which make it possible to analyze large sets of data. In other words, small data is able to bring about timely and more meaningful insights in shorter amounts of time, which is why more and more data scientists are rooting for it. This is also the reason institutes like Imarticus Learning have become popular, as they offer industry relevant training courses, in various data analytics tools like Hadoop, SAS, R and so on.

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