The Right Path to Becoming a Data Scientist: Guidelines to Keep in Mind


The data scientist is said to be eligible for a job if he or she possesses the right and required skill set and knowledge base. From the point of view of the perspectives involved in data science, it constitutes two sides:

• One is the technology side that is also related to the understanding of programming languages ​​such as R, Python, SAS, etc. And it also includes the detailed knowledge of how to handle algorithms specifically to run them in machine learning, artificial intelligence, etc.

• The other is the statistical side that is related to the handling of statistical tests such as the Chi-square test, etc. and data distributions. It also includes writing the algorithms for machine learning, etc.

Generally, while engaging in data science, the individual has to select a particular perspective out of the two mentioned above. Who wants to have higher studies in the field of statistics, look for the statistical side of data science.

Those who are interested in and love working in the technological world, since it provides a space for experimentation and innovation, opt for a technological perspective.


There is no defined right path or roadmap that one can opt for while pursuing a career in the field of data science. It usually involves advancing your skill sets from time to time so that you can handle and be able to handle more advanced and smarter tools and methodologies that are devised from time to time. You need to get your hands dirty with data and practice.


Acquiring knowledge will be of no use if you do not apply your theoretical knowledge in practice. Now the question might arise in your mind how this can be done.

This can be done by working on various projects that will guide you on how to deal with data in the corporate world. It gives you hands-on experience in handling the big data generated on a daily basis. Also, it would help you get a better and promising career in the field of data science.

Career in data science field also requires detailed and in-depth knowledge of mathematics and statistics then only you will love dealing with data and algorithms otherwise like others you will also be the leave in the middle. due to the fact that it is very challenging. Those who are attracted by the high job prospects and attractive salary packages of data scientists can never have a promising future in this field because it requires analytical skills, mathematical or statistical skills, communication skills, visualization skills, etc. All of these skills require the individual to put their heart and mind into learning them, and more importantly, numbers and coding should excite them.

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