Data science has become one of the most attractive profiles in recent years, with Harvard Business Review giving it the title of “Sexiest Job of the 21st Century.” As there is a high demand for experienced people in data science, professionals from other backgrounds have shown an interest in pursuing a career in this field. This article aims at providing a guide on how to become a data scientist and will cover the following topics:

This article covers the following topics:


What is Data Science?

Data science is a multidisciplinary field where a blend of data inference, algorithm development, and technology is used to solve analytical problems or provide insights on data. Data science can be generally divided into two groups:

Data insights – One of the main aspects of data science is to uncover findings from the gathered data. Data is as important as the person who is dealing with it. One must know how to dive into the data and find as much information from it in order to be useful.

Data products – It can be anything from software to any technical asset, which processes the data to provide meaningful information, helping form informed business decisions. Data scientists play an important role in building these data products and providing a platform where one can easily analyze the right data to get the right output.

To learn more about data science, read our blog on – What is data science?


How to become a data scientist?

One does not become a data scientist overnight. It takes a lot of learning, experience, and understanding of the concepts. Before you travel on your career journey to become a data scientist, there are some questions that you need to ask yourself:

Do you love numbers, figures, and graphs? Data science is all about numbers and figures. If you don’t like playing with numbers, you will find it frustrating later in your career.

Can you program without difficulties? Data scientists should be comfortable with various programming languages like R, Python, etc.

Are you willing to learn and start at an entry-level before reaching a proper data scientist role? If you are someone who has no experience in data analysis, you may have to start in an entry-level position.

When you have a positive answer to the above questions, you can go ahead and start acquiring the skills associated with data science.

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What are the skills required to become a data scientist?

You have to be proficient in data analysis and other related areas to become an expert data scientist. The essential skills required to start a career in data science are:

Technical Skills

Math and Statistics – Most data scientists have a background in maths, science, or statistics. It’s important to have good knowledge on various topics of statistics and maths like linear algebra, probability, and statistical analysis. If you are not from a science or math background, you can learn the basic math and statistics required in data science with the help of a professional course.

Analytical tools – To analyze data easily, there are many tools that can help in the process. Some of the prominent data analysis tools are R and SAS. These skills are highly valued in the data analytics field. You can start with Excel, as it is one of the simplest but highly-used software in the field of data analysis.

Programming languages – To create customized data analysis tools, data scientists should have a good grasp of the commonly used programming languages like Python, Java, C/C++, and Perl.

Querying languages – When the data size is huge, Excel is not enough as a platform for storage and that is why databases are used for such purposes. This is where querying languages are important. The most common querying languages used are SQL and NoSQL.

Non-technical Skills

Communication skills – Data scientists should have good communication skills to translate their technical findings to other non-technical teams or stakeholders. This way you can help non-technical teams like marketing and sales to understand your findings, with the help of which they can make informed business decisions.

Business understanding – Data scientists should have a good understanding of the business to find the right information from the gathered data. Also, their data wrangling and interpretation activities should be aligned with the business goals of an organization.

How will certification or professional training in data science help?

A majority of the data science professionals are from a science, math, or statistics background, having a master’s degree or a Ph.D.  However, to think that a master’s degree or a Ph.D. is mandatory is a misconception. One can become a data scientist without having a master’s degree or a Ph.D.

Professional training always helps and you can enjoy many benefits from it. It is great to have the above-mentioned skills. However, if you are someone who has no experience or have just started your career in data science, a certification can surely help you. It will help you to get better job prospects and improve your salary.

Naukri Learning offers a plethora of expertly curated professional certification courses in data science which will help you to boost your career and establish yourself as an expert data scientist.

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