Data Analyst vs Data Scientist: Which Career Should You Choose?

Data Analyst vs Data Scientist – Which one should you pick?

Confusing search results!

All articles you search for will tell you the same thing. Both roles are data focused, however one gets paid more and requires more maths skill. So which should you go for?

Honestly neither are "better" to go for. They are both designed for different people. One role is more focused on business decision making and reporting whilst the other is more coding, statistics and machine learning focused. It really depends on your interests, how much time you can spend and your starting point.

Breakdown

Data analysts explain what has happened and why. Data scientists predict what could happen in the future. Using an analogy – the engineer will prepare the data, the analyst will explain the data and the scientist will make predictions using the data.

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Data scientists typically get paid more but require more advanced Python, statistics and machine learning. However, it can be a good idea to start out as a data analyst.

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Salaries can vary a lot depending on the source. Use them as a rough guide.

Typically if you are a beginner, starting out as an analyst makes more sense.

30 Second Difference

Say you have a shoe selling company.

The analyst would look at the data from last quarter and say "Sales have gone down in September due to high returns for one sneaker model. Here’s the dashboard".

The scientist would create a model and say "Based on previous trends, there is a high chance these 5000 customers will stop buying next month. Here are the people to target."

Both roles are valuable. The analyst helps explain the past and current situation and the scientist will predict the future.

What does a Data Analyst do?

A data analyst will analyse existing data, clean it up, look for trends and create reports and dashboards for managers to make decisions on.

Typical Tasks:

Clean and organise data using Excel/SQL
Create dashboards using Power BI/Tableau
Answer questions such as "Which product sells the most?"
Report findings in simple language.

Tools used commonly: Excel, SQL, Power BI/Tableau and some Python.

Best for: People who enjoy solving business problems, finding trends and visualising.

What does a Data Scientist do?

A data scientist will go one step further and create models to test hypotheses. They will use statistics and machine learning to make predictions.

Typical Tasks:

Write Python code to clean and model the data
Create models to make predictions (such as customer churn)
Test hypotheses
Work with larger and messier data sets.

Tools used commonly: Python (Pandas, scikit-learn), SQL, Statistics and machine learning libraries. Core skills required are good Python, statistics, probability, machine learning and SQL skills. They also need to be able to tell stories with their data.

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Best for: People who enjoy coding, maths and testing hypotheses. They are okay with long periods of trial and error.

Comparison

	Data Analyst	Data Scientist
Main Question	What happened and why?	What will happen?
Main Skills	Excel, SQL, BI and Communication	Python, statistics, machine learning and SQL
Maths	Basic statistics	More advanced statistics and probability
Coding	Light-Moderate	Heavy
Outputs	Reports/Dashboards/Insights	Models/Predictions/Testing
Difficulty to get into	Easier	Harder
Typical Salary	Lower	Higher

This is a general view. In reality the job descriptions will overlap and many companies use the terms interchangeably.

Salary in India – What do sources say?

This is the most conflicting part of the articles. Different websites use different data and dates.

Coursera (July 2025) – On average data analysts in India earn around ₹6 Lakh per year (Base Salary). Data Scientists earn ₹12 Lakh.

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Masai School (Estimates 2026) – Data analyst freshers earn between ₹3.5-6 LPA. Data scientist freshers earn between ₹8-15 LPA.

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Glassdoor India (Guvi 2026) – Data analysts earn around ₹4.35-10.7 LPA. The average nationally is around ₹6.5 LPA. Data scientists earn around ₹10-23 LPA.

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You can see a pattern here. Data scientists tend to earn more. However, the exact amounts depend on the city, company, skills and experience. Always check the latest salaries on Glassdoor, AmbitionBox or job postings.

A final note – If you cannot pass the interviews then having a high salary won’t help. Pick the role you can realistically build skills for.

Qualifications & Eligibility

Most data analyst roles will require a minimum of a bachelor’s degree in something like computer science, data analysis or statistics. Data scientist roles will typically require more technical backgrounds and some will require a master’s degree.

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However, often having a good portfolio of projects is just as important. If you are still in 12th or early college you can start building your skills.

Quick Guide – Which one should you go for?

Go for a data analyst if:

You are a beginner or new to coding
You enjoy business, reporting and storytelling
You want to get into your first data role quickly
You have a background in commerce, arts or non-technical.

Go for a data scientist if:

You enjoy maths, statistics and programming
You are okay with long learning curves
You want to work on predictions, AI and machine learning.
You have/are building a strong technical background.

If you are unsure, go for data analyst. There is a lot of overlap in skills and you can move towards data science later.

Can a data analyst become a data scientist?

Yes! This is one of the most common pathways. As a data analyst you will have built up the core skills required for data science (SQL, data cleaning, business knowledge and communication). You would then build up:

Advanced Python (Pandas & scikit-learn)
Statistics & Probability (Hypothesis Testing & Regression)
Machine learning basics (Classification & Clustering)
Projects using predictions.

This will take a good amount of consistent learning.

Other roles to consider – Data Engineer & Business Analyst

Two other roles that are often confused:

Data Engineer – Builds and maintains pipelines and databases to provide clean data. Uses a lot of SQL, cloud tools and programming.
Business Analyst – Works very closely with the business team. Often uses Excel, SQL, Power BI/Tableau.

If you enjoy building things go for data engineering. If you enjoy working with the business team go for business analyst.

Simple Roadmap

Analyst – Excel > SQL > Power BI/Tableau > Basic Python > 3-5 Projects.

Scientist – Python & Statistics > SQL > Machine Learning Basics > Advanced Projects > Specialise.

If you are completely new to this we have a guide to getting started with data analytics (Excel, SQL, Power BI & Python). (Once this blog is published link it).

Common Mistakes

Only going for the higher paying role. This role may take years to prepare for.
Skipping the basics. Without knowing statistics and Python fundamentals you will struggle with machine learning.
Thinking the job title tells you everything. Always check the actual job description.
Collecting certificates rather than projects. Employers want to know you can do the work.
Waiting for the perfect option. Go for one and move later.

Guided Learning in Delhi

FAQs

1. What’s the main difference between a data analyst and data scientist?

A data analyst will explain what has happened using reports and dashboards. A data scientist will create models to predict what could happen. Typically data scientists will require more advanced programming, statistics and machine learning skills.

2. Which is better – data analyst or data scientist?

Neither are better overall. Data scientists typically earn more but require more technical skills. Data analysts are easier to get into and are best for those who enjoy business insights. It really depends on your interests and current skills.

3. Which earns more – data analyst or data scientist?

Typically data scientists earn more in India. Exact figures will vary depending on the city, company, experience and skills. Always check the latest data on Glassdoor, AmbitionBox or job postings.

4. What’s the salary of a data analyst fresher in India?

Different sources show varying figures. Many show around ₹3.5-6 LPA for freshers. Some show higher figures. It depends on your skills, city and company. Use as a rough guide.

5. Is data science harder than data analytics?

Generally yes. Data science requires more advanced Python, statistics and machine learning. Data analytics is more focused on Excel, SQL and visualisations. Many learners start with data analytics and progress as their skills develop.

6. Can I become a data scientist without a computer science degree?

Yes but it can be harder. Some employers will prefer technical degrees. Having a strong portfolio, good statistics and python skills and working on real projects can help you stand out.

7. Do data analysts need to know Python?

Not always. At entry level you will be using Excel, SQL and a BI tool. However it can be a good upgrade.

8. Do data scientists need to be good at maths?

Yes. To a good degree. You will need to understand statistics, probability and some linear algebra concepts to understand and trust your models. You do not need to be a mathematician but should be comfortable with numbers.

9. Can a data analyst become a data scientist?

Yes! This is a common pathway. Data analysts will have already built up skills in SQL, data cleaning and business thinking. By adding Python, statistics and machine learning and working on projects you can open the door to data scientist roles.

10. Which is better for freshers?

Typically data analyst roles are easier to get into as they require less entry level skills. Data scientist roles often require more technical backgrounds. However skilled beginners with great projects can still get in.

11. What’s the difference between a data analyst and business analyst?

A business analyst will focus on business requirements and improving processes. They will work closely with stakeholders. A data analyst will focus more on gathering, cleaning and analysing data. They do overlap and use similar tools such as Excel, SQL and Power BI.

12. Can commerce/12th pass students go into data analytics?

Yes! Many commerce students will know Excel which is a good start. Anyone can start with Excel and SQL. However some employers will prefer graduates so plan to finish your degree.

13. How long will it take me to become job ready?

Depending on how much time you have. You may need to spend several months consistently to learn the basics of data analytics. Data science will generally take longer due to the statistics and machine learning. Projects are key.

14. Where can I learn data analytics in GTB Nagar, Delhi?

Network Net Computer Institute are based in GTB Nagar, Delhi. Ask about their current courses, syllabus and request a free demo lesson. Compare how in-depth the projects are.

Conclusion

If you enjoy solving business problems, dashboards and communication go for data analyst. If you enjoy coding, statistics and predictions go for data science. If you are unsure go for data analyst. You will learn most of what a data scientist needs and can test it out.

Whatever you decide – pick a small data set this week and ask one question. This is how all data careers start.