What Is a Data Scientist? Salary, Skills, and How to Become One

Data is transforming the way business works globally. Businesses now have access to enormous amounts of data regarding sales, customer interactions, and digital experiences. This massive amount of data is expected to make businesses more data-driven.

Instead of relying on gut instinct, businesses integrate different systems to gain important insights to motivate action and drive innovation. Yet, the data doesn’t make sense of itself. A data scientist identifies the available data and determines how to use it to answer business questions effectively. If that sounds appealing, read on to learn what a data scientist is and how to become one. 

What does a data scientist do?

Data scientists combine statistics, machine learning, and computer science to turn data into actionable insights. They blend these three main areas to clean and process data and determine what questions to ask and how to answer them using data. They also build predictive models for theorising and forecasting.

A data scientist might do the following tasks on a day-to-day basis:

• Find patterns and trends in data sets to uncover insights

• Create algorithms and data models to forecast outcomes

• Use machine learning techniques to improve the quality of data 

• Communicate recommendations to other teams and senior staff

• Deploy data tools such as Python, R, SAS, or SQL in data analysis

• Stay on top of innovations in the data science field

Data analyst vs data scientist: What’s the difference?

The work of data analysts and data scientists is similar. Yet there are distinctions. While both work with data to reveal new ways for organisations to make better operational decisions, data scientists tend to have more responsibility. 

Data analysts take processed data and identify gaps, run queries, analyse information, and report findings. Meanwhile, data scientists are often expected to form their questions about the data. A data scientist might also spend more time developing models, using machine learning, or incorporating advanced programming to find and analyse raw data from disparate sources.

Data scientist salary and job growth

According to Glassdoor, a data scientist earns an average salary of  ₹15,00,000 annually in India as of January 2024 [1]. 

Demand is high for data science professionals. The World Economic Forum describes data scientists as 'among the highest in-demand roles in the labour market' [2]. In India, banking, retail, e-commerce, pharma, and automotive are major industries looking to grow their data scientist ranks [3].

How to become a data scientist

Becoming a data scientist generally requires some formal training. Here are some steps to consider.

1. Earn a data science degree.

Employers generally like to see some academic credentials to ensure you have the know-how to tackle a data science job, though it’s not always required. That said, a basic understanding of mathematics and statistics is expected. You might consider a bachelor’s degree in one of these areas or try studying data science or computer science to qualify for the field.

2. Sharpen relevant skills. 

You might also build up your technical skills by taking an online course or enrolling in a relevant bootcamp. Pursuing any of these skills can help you be more competitive:

1. Programming languages: Data scientists can expect to use programming languages to sort through, analyse, and manage large chunks of data. Data scientists in India are thought to use more programming languages than their global counterparts. Popular programming languages for data science include:

• Python

• Java

• R

• SQL

• Perl

• SAS

2. Data visualisation: Creating charts and graphs is a significant part of being a data scientist. Familiarity with the following tools should prepare you to do the work.

• Tableau

• PowerBI

• Excel

3. Machine learning: You may continuously improve data quality and forecasting capabilities by incorporating machine learning and deep learning into your work as a data scientist. A course in machine learning can get you started with the basics

4. Big data: Some employers may want to see your familiarity with big data. Some software frameworks for processing big data include Apache’s Hadoop and Spark.

5. Communication: The most brilliant data scientists won’t be able to affect any change if they can’t communicate their findings well. The ability to share ideas and results verbally and in written language is an often-sought skill for data scientists.

3. Get an entry-level data analytics job.

Since data science is gaining momentum in India, many job opportunities are available. Starting in a related entry-level job can be an excellent first step to becoming a data scientist. Seek positions that work heavily with data, such as data analyst, business intelligence analyst, statistician, or data engineer. From there, you can work up to becoming a scientist as you expand your knowledge and skills.

4. Prepare for data science interviews. 

With a few years of experience working with data analytics, you should be ready to move into data science. Once you’ve scored an interview, prepare answers to likely interview questions. 

Anticipate both technical and behavioural interview questions. Practice by speaking your answer aloud. You might also boost your confidence by preparing examples from your past work or academic experiences. Here are a few questions you might encounter:

• What are the pros and cons of a linear model?

• What is a random forest?

• How would you use SQL to find all duplicates in a data set?

• Describe your experience with machine learning.

• Give an example of a time you encountered a problem you didn’t know how to solve. What did you do?

Getting started

A data scientist career can offer an interesting challenge and a well-paying job. Plus, you’ll know that you are making a difference in the decision-making of your business as long as it’s a data-driven one like so many businesses today.

Get your start in data science with a course in the basics with IBM’s Data Science Professional Certificate.