Without a doubt, Data Science is one of the hottest career options at present and it is driving a huge number of technology enthusiasts to become a part of the community. People across the world are taking up data science courses. That is not all, people are also making transitions — moving from a different department to data science. The popularity of data science today has reached such a level that according to one of our studies, the adoption of analytics & data science at large Indian firms is around 64%. It is definitely a healthy adoption rate as most of these large firms are into traditional businesses.

However, this rise in the popularity of data science is not only creating a lot of opportunities but also becoming a competition — for both the one already working in the domain and the ones who are preparing to enter. So, the major question here is that while everyone is taking up data science courses and preparing day in and out, how would you stand out?

In order to guide you to becoming a data scientist who is elite and who stands out in the industry, we list down some of the key tips that you can follow.

Building Strong Foundation

Irrespective of the domain, a professional with strong base concepts are considered to be elite. You might have completed a sophisticated data science course paying a huge amount of money, but if your mathematical skills aren’t top-notch then you will just be a data scientist (not an elite one). So, If you want to be an elite data scientist, make sure you have a strong hand on mathematics.

There are some certain concepts in mathematics (such as linear algebra, calculus, probability, statistics, discrete mathematics, regression, optimization) that forms the foundation of data science and if you are focusing to become a top data scientist you need to gain a strong foothold. So, while everyone is busy with other concepts, make sure you start from the base and focus on mathematics. Also, make sure that the required concepts are crystal clear to you. Once you form your mathematical base, move ahead with the other steps.

Theory is important, Real-Time Experience Is IMPORTANT-ER

If you are someone who has recently completed a data science course and is all set to enter the industry as a full-time data scientist, then you might want to reconsider. Why? Because without some real time experience your towards becoming a top data scientist might get little bumpy. There is no doubt, that there is a lot of monetary benefits when you are a full-time data scientist, however, if you are planning for long term benefits, try getting an internship initially.

Try to figure out what is the core area you want to focus on before jumping right into the battleground. That is not all, internships also help you learn some of the other concepts that you might have missed during the course or which wasn’t there on the syllabus.

Master The Art Of Storytelling

While many data scientist is focusing on extracting insights from data or solving complex problems, many are ignoring the importance of data storytelling. Data storytelling is a skill where a data scientist take an idea and turn it into a story. But why data storytelling is important? Data nowadays are becoming more and more complex and even the extracted insights are not crystal clear. So, in order to bring in simplicity in it, data scientists should focus on data storytelling.

The pace at which data is getting generated on a daily basis, with time it will become more and more complicated. So, if you master the sorcery of data storytelling then you are more likely to stand out in the domain of data science.

Make Connections That Deliver Value

This point will be basically for the ones who have entered the data science domain. So, as we have already mentioned that data science is witnessing skyrocketing popularity across the world, it is becoming imperative for the existing professionals to extend their ground to for the upcoming competitors in the industry. And in order to do that, one of the things to focus on is to connect with the other leaders from the industry.

The major advantage of making connections with the leaders is that you get to know what they do to stay on top of their game. Also, another advantage is that you get to know some of the critical things from the industry that not every data scientist knows. It would help you with your works and projects in the future.

Build A Strong Public Profile

There are many top class data scientist in the industry today. However, they are not getting the recognition they deserve. So, if you think your work is getting unnoticed then you stand up for yourself and build a profile in the industry. So, how to do that? In one of our previous articles I have talked about helping startups, so you can do that. Take up different projects with startups — not based on what they would pay you, but based on what the work is and how much traction it could get you. Help them with their data issues and the more you help, the more your profile becomes stronger and more you start to get noticed.

Another way of building a strong public profile is by speaking conferences. If you have a significant amount of knowledge and experience and want to share that with a greater, enthusiastic crowd, you can always reach out for becoming a speaker at different data science conferences.