Data Science Jobs for Freshers in India: Entry-Level Roles, Skills & Career Tips

Data science jobs for freshers are gaining strong demand across India as companies depend on data insights to drive decisions. Roles such as Data Analyst, Junior Data Scientist, Business Intelligence Associate, and Machine Learning Engineer are now key entry points for graduates. These positions blend coding, analytics, and business understanding, making them among the most sought-after opportunities for beginners in tech.

In this guide, you’ll read more about the top entry-level roles, essential technical and soft skills, current market demand, salary trends, and practical career tips to land your first data science job in India. Each section helps you understand how to build a successful data-driven career from the ground up.

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Entry Level Data Science Jobs for Freshers

Below are the most common data science jobs for freshers in India, along with their key responsibilities and required skills. Each role offers a strong starting point for building a long-term career in analytics, machine learning, and data-driven decision-making.

1. Data Analyst

A data analyst is one of the most popular data science jobs for freshers. They focus on collecting, organizing, and analyzing data to help companies make informed decisions. This role suits freshers who enjoy working with numbers, spreadsheets, and visual dashboards.

Key Responsibilities:

• Cleaning and preparing raw datasets for analysis
• Performing data exploration to identify patterns and trends
• Creating dashboards and reports for management teams
• Collaborating with business teams to interpret findings

Skills Required: Excel, SQL, Python, Tableau or Power BI, basic statistics, and data visualization.

2. Junior Data Scientist

A junior data scientist is an entry-level role where freshers apply foundational data science knowledge to real-world business problems. They work under senior data scientists to collect, clean, and analyze data, build simple models, and generate actionable insights.

Key Responsibilities:

• Data collection, cleaning, and preprocessing
• Assisting in building predictive or descriptive models
• Reporting findings to senior team members
• Supporting data-driven decision-making

Skills Required: Python, R, SQL, basic statistics, data visualization, and understanding of machine learning algorithms.

3. Business Intelligence (BI) Associate

A BI Associate helps organizations turn data into insights using visualization and reporting tools. This job is ideal for data science freshers who are detail-oriented and interested in presenting complex data visually.

Key Responsibilities:

• Designing dashboards and visual reports
• Monitoring business KPIs and performance trends
• Supporting data-driven planning and forecasting
• Working with large datasets for real-time reporting

Skills Required: Power BI, Tableau, SQL, Excel, and basic understanding of data interpretation and storytelling.

Also Read: Business Intelligence 101: Key Insights, Top Tools, and Career Opportunities

4. Data Engineer (Trainee)

A data engineer trainee ensures that data flows smoothly across systems. This role is technical and focuses on maintaining databases and building pipelines that deliver clean and reliable data for analytics and modeling.

Key Responsibilities:

• Managing and structuring databases for efficient storage
• Building and maintaining data pipelines
• Ensuring data accuracy, security, and accessibility
• Collaborating with analysts and scientists for data preparation

Skills Required: Python, SQL, ETL tools, cloud platforms (AWS, GCP), and basic knowledge of big data frameworks.

Also Read: Top Big Data Skills Employers Are Looking For in 2025!

5. Machine Learning Intern / Assistant

A machine learning intern supports the development and testing of machine learning models. This position is perfect for freshers who have a basic grasp of algorithms and want hands-on experience with real-world datasets.

Key Responsibilities:

• Assisting in data preprocessing for ML models
• Implementing basic algorithms under supervision
• Analyzing model performance metrics
• Supporting automation or optimization projects

Skills Required: Python, scikit-learn, TensorFlow or PyTorch, statistics, and model evaluation techniques.

Also Read: Learning Models in Machine Learning: 16 Key Types and How They Are Used

6. Data Science Research Assistant

A data science research assistant helps with experimental projects, often in R&D or academic settings. Freshers in this role focus on data collection, hypothesis testing, and documentation of findings.

Key Responsibilities:

• Gathering and cleaning research data
• Conducting exploratory data analysis
• Supporting model validation and documentation
• Assisting in publishing research results

Skills Required:
Python or R, statistical testing, data visualization, and report writing.

Also Read: Hypothesis Testing in Statistics: Explained Simply

7. Data Operations Executive

A data operations executive manages the daily flow of data within organizations. This role bridges business and technical teams and ensures accurate reporting and data updates.

Key Responsibilities:

• Maintaining data accuracy across databases
• Validating daily reports and dashboards
• Coordinating with analysts for data consistency
• Managing automated data processes

Skills Required: Excel, SQL, attention to detail, and understanding of database management.

These entry level data science jobs for freshers act as the stepping stones toward advanced positions like Data Scientist, Machine Learning Engineer, or Data Consultant. Each role builds critical skills, data handling, analysis, and interpretation, that form the backbone of a successful data science career.

Skills Required for Data Science Jobs

To start a career in data science, you need the right mix of technical, analytical, and soft skills. Recruiters look for freshers who can understand data, write clean code, and explain their findings clearly. Even entry-level data science jobs for freshers demand a basic understanding of how to collect, analyze, and visualize information to support business decisions.

Technical Skills 

Technical skills form the foundation for any data science role. Freshers must be proficient in programming, data analysis, and basic machine learning. 

Key Technical Skills for Freshers: 

• Python: Data manipulation, analysis, and scripting for automation 
• R: Statistical computing and data visualization 
• SQL: Querying relational databases and managing structured data 
• Excel: Data cleaning, analysis, and basic visualization 
• Machine Learning Algorithms: Understanding supervised and unsupervised models, regression, classification, clustering 

Tools & Technologies 

Data science relies on specialized tools and platforms to handle, analyze, and visualize data. Familiarity with these tools increases employability for freshers. 

Essential Tools & Technologies: 

Tool / Technology	Purpose / Usage	Suggested Proficiency Level
Tableau	Data visualization and dashboard creation	Basic → Intermediate
Power BI	Business intelligence and reporting	Basic → Intermediate
Hadoop	Big data storage and processing	Basic understanding
Spark	Distributed data processing	Basic understanding
Jupiter Notebook	Interactive coding, analysis, and visualization	Intermediate

Also Read: 30 Must-Know Data Science Tools for 2026 & Steps to Pick the Right Ones

Soft Skills and Analytical Thinking 

Technical skills alone are not enough. Freshers need strong soft skills and analytical capabilities to thrive in collaborative, problem-solving environments. 

Key Soft Skills: 

• Problem-Solving: Ability to approach complex problems and find data-driven solutions 
• Communication: Presenting insights clearly to non-technical stakeholders 
• Business Understanding: Linking data insights to business outcomes 
• Teamwork: Collaborating effectively with cross-functional teams 

Also Read: Top Soft Skills for Data Science Careers in 2025

How to Find and Secure Entry-Level Data Science Jobs 

Finding data science jobs for freshers requires the right strategy, consistent learning, and an understanding of what employers look for. The demand is high, but competition is equally strong. With a focused approach and a few practical steps, you can stand out and land your first role in data science.

1. Where to Look for Entry-Level Data Science Jobs

There are several platforms where you can find data science jobs in India for freshers. Start by exploring genuine listings and internship programs to gain initial experience.

Top Platforms to Explore:

• LinkedIn: Set up job alerts for “data science fresher” or “junior data analyst.” Follow companies and recruiters.
• Indeed and Naukri: Check dedicated fresher sections and entry-level listings.
• Internshala and Glassdoor: Great for internships and trainee programs.
• Company Websites: Visit the careers pages of top IT firms, startups, and analytics companies.
• Networking: Attend webinars, online hackathons, and virtual data meetups to connect directly with hiring managers.

Also Read: The Data Science Process: Key Steps to Build Data-Driven Solutions

2. Build a Strong Resume and Portfolio

Your resume should focus on skills and projects, not just academics. Freshers often lack work experience, so your portfolio becomes your biggest strength.

Tips to Build a Standout Profile:

• Include technical skills like Python, SQL, and data visualization.
• List certifications and courses related to data science.
• Add 2–3 small projects with links to GitHub or Kaggle.
• Use data-driven results (e.g., “Built a model with 90% accuracy using logistic regression”).
• Keep it one page and easy to read.

Also Read: Data Science Resume: Complete Guide

Example Resume Snapshot:

Section	Details to Include
Skills	Python, SQL, Statistics, Tableau
Projects	Customer Churn Prediction, Sales Forecasting
Education	B.Tech / B.Sc / Certification in Data Science
Contact	LinkedIn, GitHub, Email

3. Prepare for Interviews

Once you start applying, interview preparation becomes the next big step. Most jobs in data science for freshers include both technical and behavioral rounds.

Common Interview Topics:

• Python programming basics
• SQL queries and database joins
• Statistics and probability
• Simple machine learning algorithms
• Problem-solving and case studies

Practice Platforms:

• HackerRank, LeetCode (for coding)
• Kaggle (for hands-on data challenges)
• Mock interviews through peers or mentorship programs

Also Read:60+ Most Asked Data Science Interview Questions and Answers for 2025

4. Start with Internships or Contract Roles

If full-time opportunities seem hard to find, start with an internship. Many companies convert high-performing interns into full-time employees. These roles help you build experience, confidence, and networks while improving your resume for future openings.

Benefits of Starting Small:

• Real-world exposure to datasets and tools
• Hands-on experience with projects
• Mentorship from industry professionals

Also Read: Best Data Science Course with Placement – Boost Your Career in 2025

5. Network and Learn from Communities

Networking plays a key role in securing jobs for data science freshers. Many openings aren’t advertised publicly and are filled through referrals.

Ways to Network:

• Join data science LinkedIn groups and Slack communities.
• Follow professionals sharing insights and projects.
• Attend virtual conferences, bootcamps, and hackathons.
• Collaborate on open-source data projects.

Building relationships with recruiters and mentors helps you stay updated about new openings and industry expectations.

Also Read: How Can Students Leverage LinkedIn For Better Career Opportunities?

6. Stay Consistent and Keep Learning

Getting your first break in data science might take time. Keep learning, improving your portfolio, and applying regularly. Even rejections are part of the process—each one brings clarity about what you need to improve.

Key Takeaway:
Consistency and skill development matter more than experience. By combining technical knowledge, a strong online presence, and active networking, you’ll increase your chances of landing a data science job for freshers in India faster.

Demand, Salary & Growth for Entry Level Data Science Jobs in India

The demand for data science jobs for freshers in India is steadily increasing as companies across sectors depend on data for decision-making. From startups to tech giants, every organization needs professionals who can manage, analyze, and interpret data effectively.

1. Demand Trends Across India

India has emerged as one of the top global markets for data science professionals. Thousands of openings for entry level data science jobs for freshers appear each month across job portals and company listings.

Cities with the highest demand:

• Bengaluru: Strong focus on AI, analytics, and tech-driven roles.
• Hyderabad & Pune: Growing IT and product-based companies.
• Gurugram & Noida: Opportunities in finance, consulting, and e-commerce.
• Mumbai: Hiring in BFSI, marketing, and data analytics.

Startups are also hiring data science freshers to handle small-scale projects, reporting, and automation before promoting them to advanced positions.

Also Read: Career in Data Science: Jobs, Salary, and Skills Required

2. Salary Expectations for Data Science Freshers

Salaries for jobs in data science for freshers vary by company, skill level, and city. While exact numbers differ, entry-level packages remain competitive compared to most other tech domains.

Average Salary Range in India

Job Title	Experience	Average Annual Salary (INR)
Data Analyst	0–1 year	3 – 5 LPA
Junior Data Scientist	0–2 years	4 – 6 LPA
BI Associate	0–1 year	3.5 – 5 LPA
Data Engineer Trainee	0–2 years	4 – 6.5 LPA
ML Intern / Assistant	0–1 year	5 – 7 LPA

Source- Glassdoor

What affects salary growth:

• Technical expertise: Python, SQL, and machine learning skills boost pay.
• Education: Certified courses and hands-on projects improve profiles. 
• Location: Metro cities offer 20–30% higher packages. 
• Internships: Practical experience often leads to better offers. 

Also Read: World's Top 12 Highest-Paying Cities for Data Science in 2025

3. Career Growth Path for Data Science Freshers

Starting small in data science builds the foundation for long-term growth. As you gain experience and learn advanced tools, your career path expands quickly.

Typical Progression:

• Years 1–2: Data Analyst or Junior Data Scientist – Focus on analysis and visualization.
• Years 3–5: Data Scientist or Data Engineer – Handle modeling, pipelines, and automation. 
• Years 6+: Senior Data Scientist or Manager – Lead projects and mentor teams. 

Growth depends on:

• Continuous learning and upskilling 
• Exposure to varied projects 
• Ability to communicate insights effectively 

Also Read: Data Scientist Salary in India 2025: Freshers to Experts Guide

4. Future Outlook

The future of data science jobs in India for freshers remains bright. With businesses embracing AI and automation, the demand for entry-level professionals will only rise. Reports suggest India will need over a million skilled data science workers in the coming years.

For freshers, this means a stable career path, strong learning opportunities, and high earning potential with consistent growth in skills and experience.

How Can upGrad Help in Your Data Science Journey? 

upGrad provides industry-focused programs that equip you with the essential skills to thrive as a data scientist. Their data science courses are carefully crafted in partnership with leading universities and top industry professionals, ensuring a comprehensive learning experience. With expert mentorship, personalized guidance, and a strong emphasis on hands-on learning, upGrad ensures you're fully prepared to excel in the dynamic and fast-paced field of data science. 

1. Executive Diploma in Data Science & AI -  IIIT-B 

2. Post Graduate Certificate in Data Science & AI (Executive)- IIIT-B 

3. Master’s Degree in Artificial Intelligence and Data Science- OPJGU 

4. Professional Certificate Program in AI and Data Science - upGrad 

5. Masters in Data Science Degree (Online) - Liverpool John Moore's University 

6. Business Analytics Certification Programme- upGrad 

With upGrad, you’re building a foundation for a rewarding career in one of the most sought-after tech fields. If you have any further questions, book a free career counseling call with our experts! 

References -

https://www.glassdoor.co.in/Salaries/data-analyst-salary-SRCH_KO0,12.htm

https://www.glassdoor.co.in/Salaries/junior-data-scientist-salary-SRCH_KO0,21.htm

https://www.glassdoor.co.in/Salaries/business-intelligence-associate-salary-SRCH_KO0,31.htm

https://www.glassdoor.co.in/Salaries/junior-data-engineer-salary-SRCH_KO0,20.htm

https://www.glassdoor.co.in/Salaries/machine-learning-intern-salary-SRCH_KO0,23.htm