Is Data Science a Good Career?

Data science is a strong career for professionals in India who enjoy working with data and have the required skills and educational background to succeed. The field continues to evolve, with many jobs in major cities like Bengaluru, Hyderabad, and Chennai.

Data science uses various disciplines to analyse data and develop conclusions based on that data. Many organisational departments rely on and are involved in data science projects, including marketing, information technology (IT), sales, finance, and other business-related areas. In data science, you may use different programs to create models using your data or work with data visualisation tools to present data understandably. You could also work on projects to determine the specific types of data you need to use and implement strategies to analyse that data to make recommendations to companies and organisations. 

The data science field offers many positions and varied types of work, offering multifaceted opportunities for anyone interested in working with data. Look at the work done by data scientists to see if this is a good position for you.

What is a data scientist?

Data scientists use their statistics, mathematics, coding, and analytics skills to find answers for clients within data sets. You’ll analyse data for particular problems facing your company or clients and review different data sets to determine which can help you solve an issue.

Although most of India's data science jobs in 2023 came from the banking, financial services, and insurance (BFSI) industry, data scientists can work in various fields. Data allows you to answer multiple questions to drive improved decisions, including how a company can save money, how a health care provider can best treat patients, and how to target advertising to interested consumers. Within BFSI, data allows you to better address potential fraud, optimise customer service, and improve risk mitigation.

Data scientists use various methods, software, and other tools to analyse data. Therefore, having a solid foundation in statistics, computer science, or data visualisation can be valuable in helping you start your career.

Requirements for data scientists

At the core of this job, you will collect and analyse data using programming, statistical, and IT-related skills to gain insight. Requirements can vary depending on your professional position or the tasks you’ve been assigned to analyse. You may need particular skills, education, or previous experience to stand out in the data science field.

Tasks and responsibilities

Data science is a multifaceted field requiring you to work with and analyse information. Standard tasks and responsibilities often include the following:

• Collect data from various sources

• Data preparation 

• Review data with a critical view

• Work with math and statistics skills

• Analyse different data sets to find solutions to challenges

• Use computer languages to develop data sets

• Understand data visualisation

• Maintain proficiency in various types of data programs

• Communicate conclusions clearly

Skills needed in data science

Required skills also vary from position to position, depending on what you’re needed to do for a specific position. Three standard skills you will likely need include the following:

• Coding: This skill is essential to a data science job. You may use programming languages like Python or R for data collection, data preparation, and putting your projects into production.

• Mathematics and statistics: Mathematics and statistics can help you understand your data sets, how to manipulate them for a particular application, and the best ways to visualise data.

• Computer science: Many data science applications use computers, so it’s important to feel comfortable working with detailed computing programs and data sets. Many technical skills include working with software like SAS or MATLAB and tools like SQL, which is essential for database management. You may also work with machine learning algorithms and big data.

Education and certification

It’s essential to have a solid educational foundation to stand out in data science fields. Many data science workers need a bachelor’s degree in physics, mathematics, statistics, engineering, or computer science. However, some employers prefer a master’s degree or doctorate in data science or a related field.

Certifications can help you get data science positions by sharpening your skills and providing employers with proof of your robust credentials. You may opt for specific topics, like Python or R, or certifications such as: 

• Microsoft Certified Azure Data Scientist

• SAS Certified Data Scientist

• Amazon AWS Big Data Certification

• Certified Analytics Professional

• Dell EMC Data Scientist Associate

Types of data science positions

Data science encompasses various positions, providing ample opportunities depending on your interests and background. According to Glassdoor in India’s January 2024 data, here are five data science positions you should consider, along with the average base salary of each.

1. Data analyst

Average base salary (IN): ₹6,95,775 [1]

Requirements: Bachelor’s degree or graduate degree in computer science, engineering, or a related field

The job of a data analyst is to collect and adapt large amounts of data for particular projects. You also may need to confirm the data quality or identify the data types required for a project.

2. Machine learning engineer

Average annual salary: ₹11,00,000 [2]

Requirements: Bachelor's degree or graduate degree in computer science, engineering, or a related field

As a machine learning engineer, you will use your coding knowledge to build algorithms and models to review and funnel different data sets. You may also run tests regularly to make sure systems are running correctly.

3. Statistician

Average annual salary: ₹4,26,000 [3]

Requirements: Bachelor’s degree in statistics, mathematics, or a related field

A statistician collects and organises data for projects or other assignments. You may be responsible for creating data collection methods, like surveys and polls. You might also be able to review data to conclude the information to present to a client.

4. Data engineer

Average annual salary: ₹10,80,107 [4]

Requirements: Experience with SQL and databases

Data engineers develop and maintain the infrastructure needed to generate data. This position may require you to use your programming skills or knowledge of software development to find solutions that support data scientists in doing their jobs.

5. Data architect

Average annual salary: ₹24,00,000 [5]

Requirements: Bachelor's in computer science, information systems, or information technology; experience with SQL, machine learning, and databases

A data architect creates database systems that store and analyse data for a company or organisation. You may work with software designers, data analysts, or other data science positions to ensure information is easy to access or make changes to utilise the full potential of data storage.

Is a degree in data science right for you?

Data science is a growing field as more companies and organisations rely on data and analytics to make decisions, making it a good option for those interested in pursuing a career in data science. According to 2023 data from India Today, the number of jobs in the industry will increase by 14 percent by 2026 [6].

You can work in various industries, such as health care, retail, finance, or others that may interest you and your work in data science. You can also work with companies like Microsoft, Amazon, or Flipkart.

If you are interested in data science and the related fields, such as engineering, emerging technologies, and statistics, necessary to succeed in these careers, it could be an excellent fit. 

Getting started with Coursera

Adding additional educational experience to your resume is a good option if you decide to pursue a career in data science. For example, check out the IBM Data Science Professional Certificate on Coursera, which can help you gain practical skills for everyday work in data science, including how to import and clean data sets or apply data skills for real-world problems.

You can also get a Google Data Analytics Professional Certificate on Coursera. You will learn how to use data analytical tools and visualise data to present your findings to clients and customers.