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The Anatomy of a Data Scientist [Infographics]

The Anatomy of a Data Scientist [Infographics]

Updated on 25 November, 2022

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• 5 min read

Table of Contents

What does it take to become a Data Scientist?
What are the required Technical Skills?
What are the Roles and Responsibilities of a Data Scientist?
Benefits of becoming a Data Scientist
What is the Average Salary of a Data Scientist?
Wrapping up

It is estimated that nearly 150000 Data Science jobs will be created in India in 2020. Data Science has tremendous applications across industries, and it is emerging as one of the most popular career options.

What does it take to become a Data Scientist?

The first and most important thing needed to become a Data Scientist is education. It is essential to have a Bachelor’s degree. Approximately 85% of data scientists possess a Master’s Degree, while 45% of them possess a Ph.D. To become an expert in data science, check out our data science courses from the top institutions.

Another important aspect is the specialization or the course. For instance, 32% of data scientists have a background in mathematics and statistics, 19% in computer science, and 16% in engineering. A data science course from a recognized university or institution holds your resume higher.

Explore our Popular Data Science Online courses

Executive Post Graduate Programme in Data Science from IIITB	Professional Certificate Program in Data Science for Business Decision Making	Master of Science in Data Science from University of Arizona
Advanced Certificate Programme in Data Science from IIITB	Professional Certificate Program in Data Science and Business Analytics from University of Maryland	Data Science Online Certifications

What are the required Technical Skills?

Education is a crucial requirement, but it is not the only requirement. You also need to have the right set of skills as well as a high technical aptitude.

Statistical Modelling to understand and interpret the data sets strategically.
Know at least one of the top programming languages like R, Hive, Python, SQL, and many more.
Understanding of Statistics and Mathematics
Understanding Software Engineering and Machine Learning to interpret and manage large data sets.
Understanding Artificial Intelligence to help data science in getting solutions and results for specific problems.
Data Visualization for graphical representation of data.

What are the Roles and Responsibilities of a Data Scientist?

You must pick an area of Data Science where you feel comfortable before finalizing or entering the field. Identify your proficiency and do your research.

Data Management

The work is to organize, store, and analyze data efficiently while viewing a company’s data system.

Top Data Science Skills to Learn to upskill

SL. No	Top Data Science Skills to Learn
1	Data Analysis Online Courses	Inferential Statistics Online Courses
2	Hypothesis Testing Online Courses	Logistic Regression Online Courses
3	Linear Regression Courses	Linear Algebra for Analysis Online Courses

Research and Analysis

It is the process of systematically applying logical and/or statistical techniques for evaluating data.

Refine business procedures

The old data is substituted with new data for more efficient business management.

Smart decision making and planning

Data is combined with analytics for improving decision making and planning for any business.

Generating actionable insights

Actionable insights are obtained by analyzing the raw data sets.

Simplifying the complex procedures

The complex datasets are analyzed to obtain useful data that is useful for the business.

Read: Data Scientist vs Software Developer

Read our popular Data Science Articles

Data Science Career Path: A Comprehensive Career Guide	Data Science Career Growth: The Future of Work is here	Why is Data Science Important? 8 Ways Data Science Brings Value to the Business
Relevance of Data Science for Managers	The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have	Top 6 Reasons Why You Should Become a Data Scientist
A Day in the Life of Data Scientist: What do they do?	Myth Busted: Data Science doesn’t need Coding	Business Intelligence vs Data Science: What are the differences?

Benefits of becoming a Data Scientist

The plethora of job opportunities is just one of the many aspects of choosing this field. The high-in-demand job brings the following benefits:

Data Scientist is the person responsible for uncovering the secrets that data keeps hidden. So, organizations put a high premium on the person who helps them understand trends and customer behavior.
Leading Global organizations like Amazon, Google, Apple, etc. are searching for Data Scientists.
Assured employment in the future with further enhancements of technology.
Data Science has various applications in different industries, including Consulting, Manufacturing, Healthcare, Marketing, Pharmaceuticals, Manufacturing, and many more.
According to a survey conducted in 2011, 94% of Data Science graduates have found it a satisfying job.

Our learners also read: Top Python Courses for Free

What is the Average Salary of a Data Scientist?

Harvard Business Review calls the job of Data Scientist as the “Sexiest Job of the 21st Century”. If you have a look at the average salary of any data scientist, it averages about $1,20,000 per annum.

Know more: Data Scientist Salary in India

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How upGrad helps for your Data Science Career?

Wrapping up

If you are interested in learning Data Science and opt for a career in this field, check out IIIT-B & upGrad’s Executive PG Programme in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

Frequently Asked Questions (FAQs)

1. What are the four components of a Data Science Project?

Before you are out there building your internal data science practice, it is really important to understand the structure of any typical data science project. If you miss out on any of the core components of data science, then there are high chances of failure of all the efforts you put in for bringing true value to the business.
The four main components of every data science project are:
1. Data Strategy – The development of data strategy is where you determine what data you are going to collect and why you are going to do it.
2. Data Engineering – This step is about what systems and technology you will utilize to access, use, and organize the available data.
3. Data Analysis and Mathematical Models – This is considered to be the heart of data science. Here, the data is analyzed with the help of different tools and mathematical models to extract valuable insights.
4. Visualization and Operationalization – After analyzing and modeling the available data, the data is visualized to make it easy for everyone to understand and take actions based on the conclusions drawn from the analysis.

2. What does a data scientist major in?

There are different ways to land a career in data science. If we categorize it, in general cases, there are three ways that people usually take it up.
1. Take up a bachelor’s degree in IT, math, computer science, physics, or any other related field.
2. Get a master’s degree in the data field or any other related field.
3. Directly gain experience in the data field by working in different sectors that you intend to work in.

3. Which degree is considered to be the best one for data scientists?

If you are willing to build a successful career as a data scientist, you should definitely look out to opt for Computer Science with a specialisation in Data Science. It is considered to be the most well-represented degree among data scientists, with 18.3% of professionals possessing it in the field.
This isn't really shocking because you need to possess good programming skills for building a successful career in this field. Other than that, 16.3% of data science professionals possess a degree in Statistics or Math, which is again not so surprising. It is a great option to consider if you are really good at math.