Data Science Jobs for Freshers: Entry-Level Roles, Skills, and Career Tips

Data science plays a pivotal role in helping organizations make decisions based on well-refined and accurate data, helping them grow. Its applications span across various industries, including healthcare, finance, e-commerce, and technology, showcasing its immense potential.

As businesses increasingly rely on data to stay ahead, the demand for skilled professionals continues to grow exponentially, creating ample opportunities in data science jobs for freshers. With a strong foundation in analytical thinking and technical skills, aspiring data scientists can look for a career in data science with promising prospects.

This blog aims to serve as a guide for freshers, offering insights into career opportunities, essential skills, job roles, and tips to secure a foothold in the fast-transforming field of data science.

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Why Choose a Career in Data Science?

Choosing a career in data science offers a world of opportunities and rewards for aspiring professionals, especially freshers. Here’s why this field is one of the most sought-after in today’s job market:

• High Demand: As organizations increasingly rely on data-driven decision-making, the need for skilled data scientists is growing across industries like healthcare, finance, retail, and technology.
• Lucrative Salaries: Even entry-level roles in data science come with competitive salary packages, making it an attractive option for fresh graduates. For example, the average base salary of a data scientist in India is ₹11.3L/yr.
• Growth Opportunities: Data science is a dynamic and evolving field, offering diverse career paths in areas such as artificial intelligence, machine learning, and business analytics.
• Impactful Work: Data scientists play a crucial role in solving real-world problems, from predicting market trends to improving healthcare outcomes, contributing to meaningful change.
• Global Demand: The demand for data science skills transcends borders, providing freshers with opportunities to work in global markets and a variety of sectors.

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

Data Science Jobs for Freshers in 2025

The field of data science is thriving, offering freshers a wide array of opportunities to start their careers and make meaningful contributions. Entry-level roles are designed to help beginners develop core skills, gain industry experience, and build a strong foundation in the field. Let’s explore the key job titles and roles that freshers can pursue in 2025, along with the industry-shaping positions that offer long-term growth potential.

Common Entry-Level Roles for Freshers

1. Junior Data Scientist:

• A starting point for freshers who want to dive deep into analyzing and interpreting data.
• Responsibilities include assisting in creating predictive models, identifying patterns, and conducting exploratory data analysis (EDA).
• Tools like Python, R, and SQL are essential for this role.

Also Read: Data Scientist Salary in India in 2024

2. Data Analyst:

• Focuses on examining large datasets to uncover insights and create reports.
• Responsibilities involve data cleaning, processing, and visualization using tools like Tableau, Power BI, or Excel.
• A great option for freshers looking to build analytical and communication skills.

Must Read: Data Analyst Salary in India [For Freshers & Experienced]

3. Machine Learning Engineer:

• Involves applying machine learning algorithms to real-world problems.
• Responsibilities include training models, optimizing algorithms, and integrating them into applications.
• Skills in Python, TensorFlow, and scikit-learn are highly valued.

Click Here to Read More: Machine Learning Salary in India in 2025

4. Data Architect:

• Focuses on designing data infrastructure, ensuring that systems are scalable and efficient.
• Responsibilities include setting up databases, creating data pipelines, and integrating data systems.
• A role suited for freshers with a strong understanding of data modeling and database technologies like SQL and NoSQL.

Learn More About Data Architect Salary in India

5. Business Analyst:

• Acts as the bridge between technical teams and business stakeholders.
• Responsibilities include gathering business requirements, analyzing data, and presenting actionable recommendations.
• Ideal for freshers with strong problem-solving skills and a knack for understanding business needs.

Influential Industry Roles Shaping 2025

1. Data Engineer:

• Builds and maintains the infrastructure required for data generation, processing, and storage.
• Responsibilities include designing data pipelines, integrating APIs, and ensuring data quality.
• A critical role for organizations aiming to handle large-scale data operations efficiently.

Also Read: Data Engineer Salary in India

2. Database Administrator:

• Ensures databases run smoothly by managing security, backups, and performance optimization.
• Responsibilities include database configuration, monitoring, and troubleshooting.
• Essential for maintaining secure and reliable data environments.

3. Deep Learning Engineer:

• Focuses on advanced AI techniques for applications such as natural language processing (NLP), computer vision, and autonomous systems.
• Responsibilities involve building and training deep learning models using frameworks like PyTorch and Keras.
• A role for freshers aiming to specialize in cutting-edge AI technologies.

4. Business Intelligence (BI) Developer:

• Transforms raw data into actionable insights through dashboards and visualizations.
• Responsibilities include understanding business needs, creating BI tools, and reporting data-driven solutions.
• Proficiency in Tableau, Power BI, or Looker is essential for this role.

Must Read: Business Intelligence Salary in India: Key Insights, Core Tasks, and Career Growth in 2025

5. Data Translator:

• Simplifies technical data insights and conveys them to business stakeholders in a way that drives decision-making.
• Responsibilities include interpreting complex data analytics for non-technical audiences.
• A role requiring strong storytelling and communication skills.

6. Data Privacy Officer:

• Ensures that an organization complies with data protection laws and manages data governance.
• Responsibilities include conducting audits, monitoring data usage, and implementing privacy policies.
• A role growing in importance due to increased focus on data security and compliance.

7. AI Ethics Officer:

• Addresses ethical considerations in the development and deployment of AI systems.
• Responsibilities involve creating frameworks for responsible AI use, minimizing bias, and ensuring fairness.
• A vital role as organizations prioritize trust and accountability in AI technologies.

Why These Roles Matter for Freshers

These roles offer freshers the chance to step into the data science industry and expose them to different areas of specialization. Starting with entry-level positions, they can explore diverse career paths and eventually transition into influential roles shaping the future of the industry. By understanding the scope of these roles, freshers can align their learning and upskilling efforts to match their career aspirations in data science.

Organizations Providing Data Science Jobs for Freshers

Numerous organizations actively hire freshers for data science roles, offering them a platform to begin their careers in this dynamic field. From tech giants to consulting firms, these companies provide opportunities to work on cutting-edge projects and develop critical skills. Here are a few top companies hiring data science jobs for freshers.

1. Google

• Renowned for its data-driven approach, Google offers freshers opportunities to work on innovative AI and machine learning projects.

2. Amazon

• A global leader in e-commerce and cloud computing, Amazon hires data professionals to enhance customer experience, supply chain optimization, and AWS analytics.

3. Microsoft

• Known for its advanced AI research and enterprise solutions, Microsoft provides roles for freshers in data analysis and model development.

4. IBM

• A pioneer in AI and big data, IBM recruits fresh talent for roles like data analysts, AI engineers, and data consultants.

5. JP Morgan

• A financial giant, JP Morgan leverages data science for risk analysis, fraud detection, and portfolio optimization.

6. Deloitte

• This consulting firm focuses on providing data-driven solutions, offering freshers opportunities in analytics, visualization, and business intelligence.

7. Accenture

• A leader in technology and consulting, Accenture provides a wide range of data science roles, emphasizing digital transformation and AI integration.

8. PwC

• Known for its data and analytics services, PwC hires freshers to help businesses make informed, data-backed decisions.

9. Oracle

• Oracle specializes in database management and cloud computing, offering roles for freshers to work on large-scale data solutions.

10. EY (Ernst & Young)

• EY hires fresh graduates for data analytics and consulting roles, helping clients achieve their business goals through data-driven strategies.

11. TCS (Tata Consultancy Services)

• One of India’s largest IT firms, TCS provides data science opportunities in various domains, including healthcare, finance, and retail.

12. Infosys

• A global IT leader, Infosys hires freshers for roles involving data engineering, machine learning, and business analytics.

13. HCL Technologies

• HCL Technologies offers roles in data analytics and AI development, focusing on innovative solutions across industries.

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What These Companies Look For

When hiring recent graduates, these organizations prioritize:

• Technical Skills: Proficiency in programming languages (Python, R, SQL), data visualization tools (Tableau, Power BI), and machine learning frameworks.
• Problem-Solving Ability: Capability to analyze data, identify patterns, and propose actionable solutions.
• Adaptability: Willingness to learn and apply new technologies in a fast-changing field like data science.
• Communication Skills: Ability to convey complex data insights effectively to non-technical stakeholders.

How to Get Data Scientist Jobs With No Experience?

Breaking into data science without prior experience may seem challenging, but with the right approach and dedication, it’s entirely achievable. Here are actionable steps to help freshers land their first data scientist job:

Gain Knowledge

• Master Essential Tools and Technologies:
  • Learn programming languages like Python, R, and SQL for data manipulation and analysis.
  • Get hands-on with data visualization tools such as Tableau or Power BI.
  • Explore machine learning frameworks like TensorFlow and scikit-learn.
• Enroll in Online Certifications and Bootcamps:
  • Platforms like upGrad offer specialized data science courses.
  • Opt for bootcamps that provide project-based learning and career support.

Enroll in a Bootcamp Certification in AI and Data Science and earn a triple certification from Microsoft, NSDC, and an Industry Partner

Build a Portfolio

• Work on Real-World Datasets:
  • Use platforms like Kaggle, UCI Machine Learning Repository, or Google Dataset Search to access datasets.
  • Solve data challenges and participate in competitions to showcase your analytical skills.
• Showcase Projects on GitHub:
  • Create a portfolio on GitHub to display your work, including data cleaning, visualization, and model-building projects.
  • Add detailed documentation to highlight the tools and techniques used in each project.

Leverage Internships

• Apply for Data Science Internships:
  • Start with internships in startups or smaller companies that provide hands-on experience.
  • Focus on internships that involve real-world data problems to build practical skills.
• Volunteer for Projects:
  • Offer to assist in data-related tasks for non-profits or small businesses to gain experience and references.

Network Effectively

• Connect on LinkedIn:
  • Build a professional profile highlighting your skills, certifications, and projects.
  • Engage with posts, share your learning journey, and connect with data science professionals.
• Attend Events and Webinars:
  • Join data science meetups, webinars, and hackathons to expand your network and learn from industry experts.
  • Leverage these opportunities to seek mentorship or job referrals.

Practice for Interviews

• Hone Your Technical Skills:
  • Practice coding challenges on platforms like LeetCode, HackerRank, or CodeSignal.
  • Solve case studies and prepare for common data science interview questions.
• Focus on Problem-Solving:
  • Learn to explain your thought process when approaching a data-related problem.
  • Prepare for practical tests where you may need to analyze data or build a simple model.

Read More About: Data Science Interview Questions & Answers – 15 Most Frequently Asked

Important Skills Required for Entry-Level Data Science Jobs

To succeed in an entry-level data science role, freshers need to possess a combination of technical expertise and soft skills. These skills not only help in performing daily tasks but also lay the foundation for career growth. Here’s a breakdown of the key skills required:

Technical Skills

1. Programming Languages:
   • Python: Widely used for data analysis, machine learning, and visualization.
   • R: Ideal for statistical analysis and graphical representation.
   • Java: Useful for developing data-driven applications in larger systems.
2. Data Manipulation:
   • SQL: Essential for querying and managing databases.
   • Excel: Used for data organization, calculations, and quick visualizations.
3. Data Visualization Tools:
   • Tableau and Power BI: Create interactive dashboards for business insights.
   • Matplotlib and Seaborn: Python libraries for static and dynamic visualizations.
4. Machine Learning and Statistics:
   • Understand basic algorithms like linear regression, decision trees, and clustering.
   • Knowledge of statistical concepts like probability, hypothesis testing, and distributions.

Enroll in a Free Python Libraries Certification Course and learn important Python skills, focusing on key libraries: NumPy, Matplotlib, and Pandas

Soft Skills

1. Problem-Solving and Critical Thinking:
   • Ability to analyze data to identify trends and propose solutions to business challenges.
   • Think strategically to approach complex datasets and extract meaningful insights.
2. Communication Skills:
   • Present findings in a clear and concise manner, both visually and verbally.
   • Translate technical results into actionable recommendations for stakeholders.
3. Adaptability:
   • Learn and implement new tools, frameworks, or methodologies as required.
   • Stay updated with industry trends to remain relevant in a rapidly evolving field.

Certifications to Consider

Earning certifications can boost a fresher's credibility and demonstrate their commitment to learning. Some valuable certifications include:

• Google Data Analytics Professional Certificate: Covers essential data analysis skills using tools like SQL, R, and Tableau.
• IBM Data Science Professional Certificate: Offers a comprehensive introduction to Python, data visualization, and machine learning.
• Specialized Courses on upGrad: Explore certifications in Python for Data Science, SQL for Data Analysis, or Tableau Mastery.

Earn a Free Certificate in Linear Algebra for Analysis from upGrad and upgrade your skillset!

Conclusion

The field of data science offers various opportunities for freshers, with numerous roles like Junior Data Scientist, Data Analyst, and Machine Learning Engineer paving the way for a rewarding career. As industries increasingly rely on data-driven decision-making, the demand for skilled professionals continues to rise, creating an ideal environment to explore data science jobs for freshers.

Upskilling remains key to breaking into this field. By mastering essential technical skills, gaining hands-on experience through projects and internships, and earning relevant certifications, freshers can build a strong foundation for their career. Equally important is developing soft skills like problem-solving, adaptability, and effective communication to stand out in this competitive domain.

How Can upGrad Help?

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

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