"Data is the new oil" – Clive Humby
Businesses run on data, and data scientists are the ones making sense of it all.
If you are looking to enter this exciting field, you might have questions like –
What skills do I need?
Do I need a degree?
Where do I even start?
No need to worry—we’re here to help.
In this guide, we’ll show you how to become a data scientists in just 5 simple steps.
So, let’s get started!
What is a Data Scientist?
A data scientist is a professional who specializes in working with data to extract meaningful insights. They play a key role in helping businesses and organizations –
Understand data
Make predictions
Improve decision-making
Fun fact - Data science job openings are expected to grow by 36% by 2031.
What Does a Data Scientist Do?
A data scientist collects, processes, and analyzes data to find patterns and insights that help businesses make better decisions.
Here are some common tasks they handle:
Data collection & cleaning – Gathering and refining raw data
Data analysis – Finding trends and patterns
Machine learning & AI – Building predictive models
Data visualization – Presenting insights with charts
Decision support – Using data for strategy
Technical tools – Using SQL, Python, R, and SAS
How to become a data scientist in 5 steps
Wondering how to become a data scientist?
It requires a mix of education + skills + practical experience.
Whether you are just starting or switching careers, follow these five steps to enter the field.
1. Get the Right Education
When it comes to education for data scientist, you need to focus on two things –
Earn a degree
Get certifications
A. Earn a Bachelor’s or Master’s Degree
While a formal degree isn’t always necessary, many employers prefer candidates with a background in computer science, statistics, mathematics, or data science.
So, what is the qualification required for data science:
Studies show that around –
50% of data scientists have a bachelor’s degree
And 34% hold a master’s degree
A master’s or Ph.D. in data science, statistics, or computer science can improve job prospects - especially in competitive markets.
Degree
Relevant fields of study
Bachelor’s
Mathematics, Statistics, Computer Science, Information Technology, Engineering, Physics
Master’s
Data Science, Applied Mathematics, or related disciplines
If you are pursuing a degree, focus on courses in:
Programming (Python, R, SQL)
Statistics and Probability
Data Structures and Algorithms
Machine Learning and Artificial Intelligence
B. Get Certifications
For those without a degree or those who are changing careers - online courses and certifications can be a great alternative.
Platforms like Coursera, Udemy, and edX offer data science programs that teach essential skills at your own pace.
Popular data science courses and certifications in 2025
IBM Data Science Professional Certificate
Azure Data Science Certifications
Google Data Analytics Professional Certificate
SAS Certified Data Scientist
Google Professional Data Engineer Certification
AWS Certified Machine Learning – Specialty
Applied Data Science with Python
2. Learn Skills Required for Data Scientist
You need the right skills to become a data scientist. It should be a mix of both technical + analytical + communication skills.
Top skills required for data scientist:
Let’s take a look at the key skills required to become a data scientists:
Mathematics
Multivariable calculus
Linear algebra
Statistics
Probability theory
Hypothesis testing
Descriptive and inferential statistics
Bayesian statistics
Programming
Python
R
SAS
SQL
Data Manipulation & Analysis
Data cleaning and preprocessing
Statistical analysis
Feature engineering
Data Visualization
Tableau
Power BI
Excel
Matplotlib
Machine Learning & AI
Regression
Classification
Clustering
Deep learning
Big Data Technologies
Hadoop
Apache Spark
Cloud computing (AWS, Google Cloud, Azure)
Communication
Presenting insights to non-technical teams
Writing reports and data storytelling
Understanding business problems and translating them into data-driven solutions
Pro tip - Consider joining bootcamps or online programs to gain hands-on experience in the skills required for data scientist.
3. Work on Real-World Projects
Theory alone is not enough—you need to apply what you learn. Start by working on real datasets from sources like:
Kaggle (competitions and datasets)
Google Dataset Search
UCI Machine Learning Repository
Build projects that showcase your ability to clean, analyze, and visualize data. Upload your work to GitHub or create a personal blog to share your insights. Having a portfolio makes you stand out to potential employers.
**
Read Data Scientist Resume**
4. Gain Practical Experience
Before landing a full-time data science role, gaining industry experience is essential. Here are some ways to do that:
Internships - Apply for data science internships at startups or established companies.
Freelancing - Offer your skills on platforms like Upwork or Fiverr.
Open-source contributions - Work on GitHub projects to collaborate with experienced data professionals.
Even entry-level roles such as data analyst, business intelligence analyst, or data engineer can help you transition into data science over time.
Pro tip – Visit Naukri.com to find the best freelancing and internship opportunities in data science.
5. Prepare for Data Science Job Interviews
Once you have the skills and experience, start applying for jobs. Data science interviews typically include:
Technical questions
Expect questions on statistics, machine learning, and programming.
**Example: **
What is a random forest?
What is the difference between supervised and unsupervised learning?
How does gradient descent work in machine learning?
Coding challenges
You may need to solve SQL or Python-based problems.
**Example: **
How would you find duplicate values in a dataset?
Write an SQL query to find the second-highest salary in a table.
Behavioural questions
Employers assess problem-solving and teamwork skills.
Example:
Describe a time you faced a difficult data-related challenge.
Tell me about a time when you worked with messy data. How did you clean and analyze it?
Pro tip – Use of list of the commonly asked data scientist interview questions and answers to practice.
How to Become a Data Scientist After 12th
Wondering how to become a data scientist after 12th? Follow these steps:
1. Select the right course and college (3-4 years)
Choose a B.Tech/B.Sc in Data Science, Computer Science, Mathematics, or Statistics.
Consider online degrees or diploma courses if you prefer flexible learning.
Which college is best for data science after 12th?
IIT Madras
IIT Patna
IIT Mandi
Vellore Institute of Technology (VIT)
SASTRA University
Symbiosis International University
Amity University
Loyola College, Chennai
Christ University, Bangalore
Ashoka University
Read How to Become Data Engineer
2. Learn the skills required for data scientist (Alongside your degree)
Programming: Learn Python, R, and SQL for data handling.
Mathematics & Statistics: Focus on linear algebra, probability, and calculus.
Data Analysis: Use tools like Excel, Tableau, and Power BI to analyze data.
3. Take free and paid online courses (optional but valuable)
Platforms like Coursera, Udemy, and edX offer beginner-friendly courses.
Consider certifications like Google Data Analytics or IBM Data Science for credibility.
4. Gain practical exposure through internships
Look for internships or freelance work on Naukri.com, LinkedIn, Internshala, or Upwork.
Start with Excel-based data analysis before moving to machine learning projects.
5. Join data science communities & network
Follow industry experts on LinkedIn, Twitter, and Medium.
Join communities like Kaggle forums, Towards Data Science, or Analytics Vidhya.
6. Apply for junior data roles
Look for entry-level jobs like data analyst or business analyst.
Prepare for interviews by practising SQL queries, Python coding, and case studies.
And that’s all on - how to become a data scientist after 12th.
Data Scientist vs. Data Analyst - What’s the Difference?
Both data scientists and data analysts work with data to help organizations make better decisions. However, data scientists typically have a more advanced role.
Data analysts focus on analyzing existing data to identify trends and insights based on set business goals.
Data scientists go a step further by asking their own questions, building predictive models, and using machine learning for deeper analysis.
Overall, data scientists handle more complex tasks and require advanced programming and analytical skills.
Read More About Data Scientist Vs Data Analyst
Data Scientist Salary and Job Growth
Let’s talk about data science salaries and job growth.
Salary of a data scientist in India:
As per Glassdoor 2025 data, the average salary for a Data Scientist in India is ₹13,00,000 per year, with total pay reaching ₹14,50,000 annually.
Data Scientist Salary by Experience:
Entry-level (1-2 years): ₹3,00,000 - ₹7,00,000 per year
Mid-level (3-5 years): ₹8,00,000 - ₹15,00,000 per year
Senior-level (5+ years): ₹20,00,000+ per year
Data Scientist Job Growth in India:
India’s data science market is growing at a CAGR of 57.5%.
Job listings increased by 29%, showing high demand.
11 million+ job openings expected in India in the next five years.
20,800 new data science jobs open yearly.
Why Build a Career in Data Science?
Data science offers high demand, great salaries, and strong career growth.
36% job growth – Fast-growing field with secure opportunities.
₹1300000 average salary – Competitive pay, even for beginners
11 million job openings – Huge demand across industries.
Wrapping up
And that’s a wrap on – “how to become a data scientist?”
It takes dedication, but by learning key skills + working on projects + gaining experience, you’ll be ready for a successful career in data science.
And if you are looking for data scientist jobs in India? Find the best openings on Naukri.com.
FAQ
-
What educational background is required to become a data scientist?
While a bachelor's degree in a quantitative field such as computer science, mathematics, statistics, engineering, or physics is a common starting point, having a master's or Ph.D. in data science or related fields can enhance job prospects and opportunities. -
Are there any online courses or certifications for data science?
Yes, there are numerous online courses and certifications available on platforms like Coursera, edX, Udacity, and others that offer comprehensive data science training. -
Do I need to know programming to become a data scientist?
Yes, programming is a fundamental skill for data scientists. Learning languages like Python or R is essential for data manipulation, analysis, and building machine learning models. -
What kind of projects should I work on to become a data scientist?
Aspiring data scientists should work on projects that involve data cleaning, analysis, visualization, and machine learning. Personal projects that demonstrate practical skills and problem-solving abilities can be a valuable addition to your portfolio. -
Is a data science internship necessary to get into the field?
While not mandatory, a data science internship can provide valuable real-world experience and exposure to industry practices. It can enhance your resume and increase your chances of landing a full-time data scientist role. -
What are the typical interview questions for data science positions?
Data science interviews often include technical questions related to programming, statistics, and machine learning. Behavioral questions may assess communication skills and ability to work in a team. Sample problems and projects may be given to evaluate problem-solving abilities. -
How can I keep up with the latest trends and advancements in data science?
Staying up-to-date in data science requires continuous learning. Follow industry blogs, attend conferences, read research papers, and participate in online communities to keep yourself informed about the latest trends and technologies.
