Data Scientist: Scope, Salary, Skills, And How To Become One

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By Hrishi

We live in a world where we are dealing with data and information; processed data conveys a piece of information to us. Based on that information, we can make some collective decisions.

As the world erupted in sharing and consuming a piece of information, marketers, especially in the business world, discover new ways to understand and use that wealthy information for their own good.

As humans enter a high-level digital communication world, information begins to be consumed, interpreted, and generated at a different level. In today’s world, the end-user has created a social media profile; they buy insurance online, read blogs, etc.

These are the various mediums through which data is generated, transferred, and utilized at a lightning speed.

Now to deal with enormous amounts of unprocessed and unevenly distributed data as it is being created is a big task. For many companies, the value of this raw data means their business lifeline because they can make very precise decisions once they derive the meaning out of that raw data.

With this void of how the companies will get a well-managed and simplified form of data, the Data Scientist came into the picture. What exactly is a Data Engineer or a Scientist? We will find out.

Who is a Data Scientist?

Being a Data Scientist is the most important part of this whole puzzle. As mentioned earlier, data is being generated worldwide at a pace which takes a lot of work to maintain.

Data scientists worldwide use their analytical, mathematical, data interpretation, and computer science skills to help various global businesses and companies make precise decisions, which will help their businesses and help them grow as brands.

What does a Data Engineer do? Skills

Data scientists is responsible for making an easily predictable` model so that they can successfully predict the data pattern and forecast the data. This information is more simplified on which decisions of many companies depend. Data engineers use all their skills while doing that; on a daily basis, you can expect these tasks to be performed as a data engineer.

  • A Data Engineer is mostly responsible for discovering patterns from the unprocessed raw data. They then understand the pattern that data is showing. To be able to discover all this, a Data Engineer uses various platforms, mainly in Structured Query Language or SQL.
  • While using all these SQL platforms, a data engineer is responsible for creating different algorithms and has to create various data models in order to interpret the data successfully. The data interpreted by the Data Engineer does not convey a piece of proper business information at all so they sometimes have to dig very deep in order to find a proper rend so they are able to convey it in a simpler term to their clients.
  • A Data Engineer uses various machine learning techniques in order to improve the quality of the data under observation so that meaning can be derived from it.
  • Among the team, Data Engineer may act as a bridge between the client and the company stakeholders. They need to communicate and make each of them understand the interpretation. Based on that interpretation, some well-precise business decisions can be taken.
  • There are various tools that are available in the market that may help a Data Engineer to elaborate the meaning of data successfully. If we talk about open source, there is R language; then we have closed source software like Statical Analysis System or SAS. SAS and R are software that is used to do advanced analysis, Multivariate evaluation, knowledge management & check advanced analytics.
  • While doing it all, a Data Scientist should be in good command and not be overwhelmed by a huge amount of data; this may impact analytical interpretations.

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How to Become a Data Scientist?

Get a Relevant Degree or Do a Diploma/Certification Course

Finding a dedicated course that teaches you about being a Date Engineer or Scientist is very hard. The first thing you need to test in yourself is the necessary analytical drive, good mathematical interpretations, forecasting things, and being well aware of computer science.

Once you are confirmed to do all this, you need to do different courses or relevant certifications so that you can enter this field.

Some of these certified courses are,

Google Data Analytics Professional Certificate.

Course Duration- 1-3 months

Fees- $39 per month

Microsoft Certified Azure Data Fundamentals

Course Duration 1-3 months

Fees- $99

Oracle Database SQL certified associate certification

Course Duration 1-3 months

Fees- $99

Develop Relevant Skills

Being a data scientist, you should have very good analytical skills with computer programming. As we proceed, we will discuss some other skills and platforms you need to use while being a Data Scientist.

There are a few basic programming languages a data scientist should be well versed in. These helping tools and the programming languages will help them analyze and manage the data.

A Data Scientist should also be able to represent the interpreted data pictorially. Data in the form of graphs and charts are easy to understand. Some popular programming languages and data visualization tools are.

Programming Languages

  • Python
  • R (open source).
  • Structured Query Language or SQL.
  • Statical Analysis System or SAS.

Data Visualization Tools

  • Tableau.
  • PowerBI.
  • Microsoft Excel
  • Apache Hadoop
  • Spark

Being able to execute machine learning is very necessary for a data scientist. They have to draw a meaning after understanding the pattern of the data. Machine learning is also helpful in forecasting and day-to-day work.

You should know how to deal with Big Data and proficiently use Hadoop Apache Spark.

A Data Scientist needs to be a good communicator. If you are able to communicate your findings and convey them to the stakeholders successfully, you will be considered a good data scientist.

You need to have the necessary leadership skills. A data scientist is one who manages the team as well as the stakeholders within the company and is answerable to the client.

Get an Entry-Level Job and Gain Some Experience

Getting industry experience is considered a big boost in the field. You can join as an intern in a company that works in Data Analytics.

  • The last part will be preparing for the interview and starting your career in this field.

Average Salary to Expect Once You Become a Data Scientist

According to a recent survey, the salary benefit of a Data Scientist in the United States of America is $145866 per annum.

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