All kinds of organizations ranging from retail to government, to healthcare heavily depend on data scientists. Over the next decade, the U.S. Bureau of Labor Statistics estimates a 22% growth for data science job openings all the way through 2030, which far exceeds the 7.7% projected increase for all other occupations.

That directly translates to an average demand of about 3,200 more data scientists each year until 2030. The increase in data are prompting organizations to be on the lookout for highly skilled data science professionals as they turn toward data-driven decision-making.  

Hence, it is quite clear that data scientists play a vital role, one that is only projected to continue to increase in value and importance over time. If you’re here, then it can be assumed that you are on a mission of deciding your career path. In this blog, we will help you make a well-informed decision on data science career path, so keep on reading. 

What are Data Scientists?

Data scientists are professionals who are capable of organizing and analyzing raw data from various sources, enabling these organizations to make well-informed decisions that boost profitability and fuel growth efficiently.

They use data to understand and explain the phenomena around them, and help organizations make better decisions. Working as a data scientist can be intellectually challenging, analytically satisfying, and put you at the forefront of new advances in technology.

Basic Skills You Should Know for Data Science

There are few skills which you should definitely know before getting into data science. Few of them are stated below:

• Mathematics & Statistics
• Computer Science
• Python
• Data Analysis Tools
• Data Visualization
• Machine Learning
• Deep Learning
• Artificial Intelligence
• Data Mining
• Data Wrangling

Before we move into the next section, ensure you have a good grip on data science essentials like Python, MongoDB, Pandas, Numpy, Tableau & PowerBi Data Methods. If you are looking for a detailed course on Data Science, you can join GUVI’s Data Science Career Program with placement assistance. You’ll also learn about the trending tools and technologies and work on some real-time projects. 

Additionally, if you want to explore Python through a self-paced course, try GUVI’s Python self-paced course.

Job Growth and Salary Statistics in Data Science 

The numbers are evidence of the extraordinary growth of data science. In 2022 itself, 137,000+ jobs were made available in the data science field.

It is stated that India will have captured about 32% of the Big Data market worldwide by 2026. Read about how Data Science is a bankable career for Indian youth and that the market is set to grow to an outstanding USD 322.9 billion by 2026 in this TOI article – Data Science: A bankable career path for Indian Youth 

Hence, it’s a no-shocker that the average data scientist salaries in India range from INR. 4LPA to INR 20LPA with an average of INR 9.4LPA according to Glassdoor. It indeed is in high demand and a great career path to follow. Now, let us discuss the various data science career roles and paths. 

The Different Career Paths: Data Scientists Role

Data science is an extensive field and beholds a range of different paths and career options. It is natural to be overwhelmed with these choices and unsure about a specific path that would be for you. We are here to help. First, let us discuss about different data science roles and then dive into the career path specific only to a Data Scientist. 

1. Data Analyst 

The Data Analyst role is considered to be an “Entry level” opportunity in the data science domain. Data Analysts collect information from different sources, analyze its patterns and present it to stakeholders in an intuitive way. They recommend various techniques and methods that can help a company make business-critical decisions and improve efficiency. 

2. Data Manager  

Data Managers are responsible for managing and sometimes even building data systems following the specifications of Data Architects. Their main goal is to store and organize data whilst ensuring its security and confidentiality.  

3. Data Architect  

Data architects are experts who design and create blueprints for all kinds of data management systems. An organization’s data system and infrastructure must be built and maintained by identifying possible installation and structural problems as well as their solutions. Data architects must ensure that their organization’s data solutions are built for scalability and performance. 

4. Data Engineer 

Another very famous career path for a data scientist, data engineers are responsible for designing, creating, nurturing, and managing data pipelines that are used for making information available to data scientists at all times. They must also create new and advanced solutions in order to support the increasing data complexity, working closely with front-end and back-end developers, product managers, as well as analysts.  

5. Business Analyst  

Business analysts are very similar to Data analysts, with some fundamental differences in their functioning and data operation. They are experts in the business domain, how it functions, and its processes; analyzing and preparing meaningful insights by diving deep into the data. They help data analysts and impart business insights to them. 

A Data Scientist’s Career Path 

As we discussed above, there are many different roles and responsibilities in the data science field but now we will focus on a data scientist’s career path which is divided into various levels such as: 

• Junior Data Scientist 
• Mid-Level Data Scientist 
• Senior Data Scientist 
• Data Science Manager 

1. Junior Data Scientist 

This is an entry-level job role that is usually held by a recent university graduate having less than two years of work experience.  

Junior data scientists work on the very basic aspects of data analysis, which include extracting, cleaning, loading, and integrating data. With a focus on predictive analysis, they make use of pre-existing statistical models and work with the specifications laid out by a senior data scientist. 

Salary in India: 7 LPA

Roles and Responsibilities of a Junior Data Scientist:

• Basic problem-solving skills
• Proficient in writing SQL queries
• Performing analysis R as well as MS Excel
• Data Visualization
• Creating interactive dashboards

2. Mid-Level Data Scientist 

After gaining some industry experience as a Junior Data Scientist, you will be able to advance and become a Mid-Level Data Scientist. Most data scientists at an organization, fall under this category. These professionals are responsible for driving a project forward whilst working under senior data scientists. 

Salary in India: 12 LPA

Roles and Responsibilities of a Mid-level Data Scientist:

• Building complicated models along with a senior data scientist
• Data Analysis

3. Senior Data Scientist 

After consistent performance over a number of projects that you can properly manage junior data scientists whilst juggling your tasks, you will be able to bag a promotion as a Senior Data Scientist. 

This role is like taking the first step toward team and project management because now you play a supporting role in your workstream and also report to the data science manager as well as the client. 

Salary in India: 24 LPA

Roles and Responsibilities of a Senior Data Scientist:

• Understand, draft, storyline, and communicate data solutions
• Solid understanding of how various outputs of the team will finally integrate into the project
• Lead a few junior data scientists

4. Data Science Manager 

After working as a senior data scientist, you can advance your career in many other ways by going to research or other related fields but the most popular and in demand is by advancing to a managerial position. 

Data Science Managers play the role of advisors in all the projects that are going on within the company and are data-oriented. They are not always put on a specific project, and are responsible for ensuring quality control and that the best practice processes are being followed in all of the projects. 

Salary in India: 32 LPA

Roles and Responsibilities of a Data Science Manager:

• Efficiently lead a team
• Look after various business parameters

Kickstart your Data Science journey by enrolling in GUVI’s Data Science Career Program where you will master technologies like MongoDB, Tableau, PowerBi, Pandas, etc., and build interesting real-life projects.

Alternatively, if you would like to explore Python through a Self-paced course, try GUVI’s Python Self-Paced certification course.

To Wrap Up

Data science is one of the most demanded jobs of this decade and this demand will always keep increasing. There are various ways to get into data science career, you have to choose one as per your comfort. With the rising awareness about the field, there is immense competition in securing jobs amongst professionals.  

However, if you follow this guide and start early with the right resources, you are sure to succeed in this field and find your place. Just keep in mind, picking the right career path for yourself is just a start; your actual journey of learning starts after that. 

FAQs

What is the career path for data scientist?

The career path for data scientist includes progress in roles, learning new skills and gaining responsibilities as you rise through the ranks. The US Bureau of Labor Statistics estimated that the employment rate for data scientists will grow by 36% from 2021 to 2031.

What is the next position after data scientist?

Some of the positions that you gain after data scientist:

Data Science Manager
Data Science Team Lead
Machine Learning Engineer
Data Architect
Product Manager

What is the average salary of a data scientist?

The average salary of a data scientist in India is INR 12.8 LPA which also varies as per the skills, experience, location, etc.