How To Start A Career In Data Science

A data scientist is someone who helps an organisation to make critical decisions through data analysis, modelling, visualisation, among others. According to the survey reports, data science and analytics ecosystem has been witnessing an overall growth in the number of jobs with India contributing to 6% of open job openings worldwide. 

Currently, the total number of analytics and data science job positions available are more than 90,000 and compared to the worldwide estimates, India contributes 6% of open job openings. In this evolving talent market, aspirants have been developing a blend of skills in order to strive ahead in the role of data science.

While taking this journey, there are a few crucial questions that keep roaming inside the head. For instance, what are the most essential tools? which path to follow? What new can you learn? among others.   

Today, this article attempts to evaluate all these crucial questions and will take a more in-depth look at how to choose the right career in Data Science. Here, we list down 7 points following which an aspirant will inevitably move in the right direction.

In order to become a good data scientist, an aspirant must have blended knowledge of BI tools, cloud solutions, visualisation tools, programming languages, data management tools, among others. Languages like Python, Java, R, SQL continue to dominate the market as the tools of choice among the data analysts and data scientists. According to reports, almost 17% of all advertised analytics jobs in India demand for Python as a core skill whereas 16% demand Java. R skills come third in the most critical skills required with 10% of all analytics jobs looking for R professionals.

The Data Science domain is huge and one needs to be clear in the head as which role to choose and start preparing accordingly. There are a number of job roles in data science which are currently available among organisations such as machine learning engineer, data architect, quantitative analyst, Big Data engineer, data scientist, adat visualisation expert and several others. One must get clear what these job roles do and then decide what you should become.  

With the numerous amount of data gathered every day in the organisations, Big Data has gone through significant disruptions in these few years. According to reports, the analytics industry has grown to $3.03 billion in size last year and is expected to double by 2025. One must learn to implement Big Data techniques using tools such as Tableau, SQL, NoSQL, Hadoop, Pig, Hive, among others.