Build a Successful Career in Data Science

How do you usually start your day? Let us take a guess. You probably hit the snooze button at least 2 times before you open your eyes. The next few minutes are probably spent checking how many ‘likes’ or ‘retweets’ your post from last night managed to get. If nothing, you probably just look at the trending stories before getting started with the long day ahead. Ever wondered how and who decides what the ‘trending’ story should be?

Well, while you were enjoying your much-deserved sleep, the data scientists at Facebook and Twitter were working hard to analyse millions of posts as well as Tweets to figure out what most people are talking about. All of this (analytics) is a component of data science. It won’t be wrong to say that analytics is like the art of storytelling. It helps in finding hidden insights and is an indispensable part of data science.

So what is data science?

To put it in simple words, data science is the analysis and systematic study of facts. Now, these facts may be segregated into several categories like structured data, semi-structured data, and even unstructured data.

Though data science is a relatively new term, it has been around in several forms for decades now. So about 5-7 years ago, you had several experts like a computer scientist, a programmer and a statistician working on data collection, classification, and analysis. Now, you have one data scientist handling the tasks that were previously split between several domain experts.

It does not mean that computer scientists, programmers, and statisticians do not have anything to offer anymore. They still take care of building software (which is used to collect data from multiple sources), coding models, and application of data collection tools and methods respectively. A data scientist takes care of collecting and storing data pulled in from several sources, analyzing and visualizing the data, and finally deriving insights from it.

Need for data scientists

As per a report by NASSCOM, the analytics industry in India is expected to go from $2 billion to $16 billion by 2025. By 2018, there will be a shortage of 190,000 trained data scientists in the US, while the demand and supply gap for data science professionals in India has already peaked to 2 lakhs.

There is a huge demand for data science and analytics professionals in fields like:

• Banking
• Retail
• Telecom
• Healthcare
• Manufacturing
• Energy, and
• Logistics

Why is the right time to become a data science professional?

Well, the answer is pretty simple. Data Scientist has been named the hottest job of the 21st century for a reason, so there could be no better time to build a career in this field. As per the Analytics India Industry Study of 2016:

• Close to 8500 data science professionals (with no prior experience) joined the Indian analytics workforce in 2015
• About 46% of Indian analytics professionals have less than 5 years of experience while only 19% of them occupy senior positions
• Almost 56% of analytics professionals have a Master’s degree
• Entry-level professionals in the field can expect an average salary of 4-6 LPA, while those with the knowledge of R can earn as much as 10.20 LPA.
• Analytics is mostly used in areas like Business Intelligence/Dashboard/Reporting
• Concepts like Big Data and Advanced Analytics have not yet been fully explored, signifying the amount of growth expected in the analytics industry in the coming years.

These statistics prove that if you have a passion for examining data and want to get paid well for it, then data science is the field for you. Do you already have a job and are wondering if you can make a fresh start in this field? Well, luckily for you, data does not discriminate. So take up a full-time or part-time course in data science to pave way for a fulfilling career ahead.