X
Phone rotate NU is all about fresh perspectives. So is our website.
Watch us in portrait mode to discover what makes us different.
whatsapp logo Phone logo1800 103 5050
NIIT UNIVERSITY

Data Science jobs for freshers – A beginner’s guide

“Are there data science jobs for freshers?”

We often hear this question from students who aspire to take up a specialization in Data Science.

In this beginner’s guide, we’ll explore the job opportunities available for freshers in data science, what the jobs involve, what skills you need and what you can expect from a career in data science. We’ll list down names of the companies in India that are proactively hiring data science talent. And, we’ll also offer some helpful tips to land a good job if you are a fresher in data science.

For this guide, we’ve used the Q&A format to answer all the questions that you may have about the scope of data science.

1. What is Data Science?

Data Science is one of the hottest fields for aspiring young minds, currently. It deals with the collection, processing, analysis, and interpretation of data to solve complex problems. With the exponential growth of data, the demand for skilled data scientists has increased tremendously.

2. What’s the scope of Data Science in India?

Industry reports suggest that the demand of data scientists is at an all-time high in India. According to Analytics Insights, India is expected to generate a whopping $20 billion by 2026 by commanding 32% of the big data market. Analysts also predict that by 2026, there will be around 11 million job openings in the Indian data science industry.

3. What jobs are available for Data Science freshers?

Data Science is a highly sought-after field, and every day new job opportunities are being created for freshers. In this section, we’ll explore some of the most popular data science jobs for freshers and the other senior profiles they can move into as they progress in their careers.
  • Data Analyst
    Data Analyst is the most popular entry-level job profile in the field of Data Science. It involves collecting, processing, and performing statistical analyses on large datasets to extract insights that can help businesses make informed decisions. The job responsibilities of a Data Analyst include data cleaning, data visualization, report generation, and making recommendations to stakeholders.

    To become a data analyst, you need to have the requisite knowledge of statistical software, such as R, Python, and SQL. You also need to have a good understanding of data analysis techniques and business acumen. Data analysts typically require a Bachelor’s degree in a relevant field such as Computer Science, Mathematics or Statistics. In India, the average salary for a Data Analyst in India is around 4-5 lakhs per annum.
  • Business Intelligence Analyst
    Business intelligence analysts are responsible for analysing large sets of data to provide insights that help businesses make informed decisions. They work with various stakeholders in an organisation to provide insights and recommendations based on their analysis. The job requires strong analytical skills, expertise in data analysis tools such as SQL, Python, and R, and the ability to communicate insights effectively to non-technical stakeholders.

    As a fresher, you can start your career as a Business Intelligence Analyst in various industries such as retail, finance, healthcare, and e-commerce.. The average salary for a Business Intelligence Analyst in India is around 6-7 lakhs per annum.
  • Data Visualization Specialist
    Data visualisation specialists are responsible for creating compelling visualisations of large sets of data to help stakeholders make informed decisions. They work with various stakeholders in an organisation to design and build dashboards and visualisations that provide insights into complex data sets. The job requires expertise in data visualisation tools such as Tableau, Power BI, and D3.js.

    As a data science fresher, you can start your career as a data visualisation specialist in industries such as e-commerce, finance, healthcare, and consulting. The average salary for a Data Visualization Specialist is 10-12 lakhs per annum.
  • Data Scientist
    Data scientists are in great demand. A data scientist’s role involves working with large datasets, developing predictive models, and providing insights that can help businesses make informed decisions. The job responsibilities of a data scientist include data cleaning, exploratory data analysis, feature engineering, model selection, and evaluation.

    Data Scientists need to have a strong foundation in statistics, programming, and mathematics. To become a Data Scientist, you will typically require a Master’s or PhD degree in a relevant field such as Mathematics, Statistics, or Computer Science. If you are a data science fresher and want to take the path to becoming a Data Scientist, you need to consider doing a Master’s degree and then move on to doing your PhD. In addition, you also need to have a good understanding of machine learning techniques, data visualisation, and business acumen.

    The average salary for a Data Engineer in India is around 6-15 lakhs per annum.
  • Big Data Engineer
    Big data engineers are responsible for designing and building big data infrastructure that can support the storage and analysis of large volumes of data. They work with big data technologies such as Hadoop, Spark, and NoSQL databases. A fresher aspiring to become a big data engineer must have a strong foundation in programming and data structures. Knowledge of big data technologies and distributed systems is essential for a big data engineer. A big data engineer works with data scientists and analysts to create databases, data pipelines, and other systems that enable the efficient processing of big data.

    Taking up a position as a big data engineer is an excellent option for data science freshers. Do keep in mind that it requires a sound understanding of big data technologies such as Hadoop and Spark. The average salary for a Big Data Engineer is 10-15 lakhs per annum.
  • Data Engineer
    A data engineer is responsible for designing and building data infrastructure that can support the storage and analysis of large datasets. They work with data scientists and analysts to create databases, data pipelines, and other systems that enable the efficient processing of data. The role of a data engineer is an excellent option for freshers who have strong programming skills and a deep understanding of data infrastructure. You may work with senior data engineers and learn about various data storage and processing technologies. The job requires expertise in data modelling, database design, and programming languages such as Python, Scala, and Java.

    To become a Data Engineer, you will need a degree in Computer Science or a related field. As a data science fresher, you can start your career as a Data Engineer in industries such as e-commerce, finance, healthcare, and consulting. The average salary for a Data Engineer in India is around 15-20 lakhs per annum.
  • Machine Learning Engineer
    Machine Learning engineers are responsible for developing algorithms and models that can learn from data and make predictions or decisions to solve complex business problems. They work on projects such as predicting customer behaviour, fraud detection, and so on.

    The job involves working with large datasets, developing and testing algorithms, and deploying models in production. The role requires a deep understanding of machine learning techniques, programming languages like Python, Java, and C++. To become a Machine Learning Engineer, you need to have a degree in Computer Science or a related field and experience in machine learning and software development.

    A data science fresher looking to become an ML engineer must have a good understanding of ML algorithms, data structures, and programming languages like Python or R. The position of an ML engineer is a challenging and rewarding one for freshers who are passionate about machine learning and have strong programming skills. The average salary for a Data Engineer in India is around 20-25 lakhs per annum.
  • Data Architect
    A data architect is responsible for designing and managing an organisation’s data architecture, including data models, data integration, data storage, and data governance. They work closely with data scientists, engineers, and analysts to ensure that data is accurate, accessible, and secure. There is a sudden surge in the demand for data architects today.

    As a data architect, one must have strong technical skills in data modelling, database design, and data warehousing. Additionally, they need to possess excellent communication and leadership skills to collaborate with cross-functional teams and effectively communicate complex technical information to non-technical stakeholders.

    If you are a data science fresher who wants to progress into a Data Architect, you will need to have experience in data engineering or data science and in a data science solution delivery role. The average salary for a Data Engineer in India is around 20-25 lakhs per annum.

4. Which companies in India are hiring Data Science talent?

Data Science is emerging as one of the most popular career options for freshers with a background in Computer Science, Mathematics & Statistics. India is expected to create 11 million jobs by 2026 in the field of Data Science. From e-commerce, tech companies to financial services, from pharmaceuticals to automobiles, a lot of companies in India have been proactively hiring Data Science freshers and experienced people. Here’s a list of those companies that you must keep a tab on if you are a Data Science fresher:
  • Amazon: This e-commerce giant is heavily invested in data science and continues to hire data science talent from freshers to experienced people.
  • IBM: This global technology and consulting offers a range of data science job opportunities, including data scientist, data analyst, machine learning engineer, and data engineer.
  • TCS: India’s largest software company is betting big on data science and has created an industry-leading data science division. As the company expands further into data science, they are proactively hiring for the roles of data scientist, data architect, data engineering, data scientist, data analyst, ML engineer and so on.
  • Infosys: As one of India’s largest IT companies in India, Infosys is at the forefront of data science and analytics. Infosys has a very strong data science team, and they are always on the lookout for talented professionals who can help them leverage data to drive their business forward. The company continues to hire young and fresh data science talent at the levels of data analyst, data scientist, ML engineer, data architect, and business analyst.
  • Google: This big tech company has been hiring the best talent in the field of data science and offers a wide range of data science job opportunities in India. Some of the key roles that are available at Google include data scientist, data engineer, machine learning engineer, and analytics manager.
  • Microsoft: Known for its innovative products and the recent AI/ML craze ChatGPT, Microsoft offers a wide range of job opportunities in India. Some of the key roles that are available at Microsoft include data scientist, machine learning engineer, data analyst, and data engineer.
  • Mu Sigma: This leading data analytics firm, founded in India, is a trailblazer in data science and analytics. The company has a very strong data science team, and they are always on the lookout for talented professionals who can help them leverage data to drive their business forward.
  • Fractal Analytics: This top data & analytics firm has been doing cutting-edge work in the fields of data science and analytics. The company continues to hire people across all levels in data science. Current openings include data scientist, ML engineer, data analyst and so on.
  • Other Tech & Consulting Companies: Many other tech and consulting companies have upped their game on data science and are currently hiring a lot of talent across the seniority spectrum. These include: Accenture, Deloitte, Cognizant, KPMG, Databricks, Alight Solutions, Principal Global Solutions, GlobalLogic, etc.
  • Other Sectors: If tech companies are on a data science talent hiring spree, other sectors are not too far behind. Many leading organisations from across the board including pharma, financial services, FMCG, mobility and more are currently hiring for data science roles. Some of these companies include: Fidelity International, S&P Global, Pfizer, Uber, Jubilant Ingrevia Limited, Eli Lilly and Company, Dyson, Bloom Energy, Axis Bank, and so on.

5. What skills do you need to succeed in a Data Science career?

Whether you are starting out as a data science fresher or want to become a seasoned professional, a career in data science requires you to have a combination of technical, analytical and business skills. Here are some essential skills required for data science jobs.

Let’s look at the hard (professional) skills first:

  • Statistics: Understanding of statistical concepts and methods such as regression, clustering, and hypothesis testing is crucial.
  • Machine Learning: Knowledge of machine learning algorithms, models, and techniques such as Random Forest, KNN, SVM, and Deep Learning.
  • Data Visualization: The ability to visualise data in a meaningful way using tools such as Tableau, Power BI, and QlikView.
  • Communication Skills: The ability to communicate complex data-driven insights to non-technical stakeholders.

A data science professional, whether a fresher or an experienced person, also needs soft (human) skills too such as:

  • Analytical thinking
  • Problem-solving skills
  • Attention to detail
  • Communication skills
  • Time management skills
  • Negotiation skills
  • Resourcefulness
  • Teamwork skills

6. What should a Data Science fresher look for in a Job?

Many companies are looking for fresh data science talent to fill their vacancies. However, as a data science fresher, you must look for specific things in a job that will help you to succeed and grow in your career. Here’s a list of important things to consider:

7. How do interested freshers land a job in Data Science?

Although there is an increasing demand for data science freshers, not all freshers make end up getting an offer letter. Companies are looking to invest in people who stand out. Here are some tips you could follow to land that perfect job in data science:

  • Start with the basics
    The first step to landing a job in data science is to understand the basic concepts of the field. You need to have a good understanding of statistics, programming, and data analysis. Make sure to brush up your skills in these areas before you go for an interview.
  • Build your portfolio
    As a fresher, you may not have any work experience in data science. However, you can showcase your skills by building your own portfolio, in case you have done an industry project or internship while studying. You can also work on personal projects, participate in online competitions, or contribute to open-source projects to show your potential employer what you are capable of.
  • Network
    Networking is crucial in any field, and data science is no exception. Attend conferences, meetups, and events related to data science to build relationships with other professionals in the field. You can also connect with people on social media platforms such as LinkedIn, Twitter, and GitHub.
  • Find a mentor
    Having a mentor who is experienced in data science can be highly beneficial. A mentor can provide you with guidance on the skills you need to develop, the projects you should work on, and can also introduce you to potential employers.
  • Customize your resume and cover letter
    When applying for jobs in data science, make sure to customise your resume and cover letter for each job you apply for. Don’t forget to specify your relevant skills and experience, by using keywords that match the job description. Also, make sure to include your portfolio and any other relevant information that can make you stand out.
  • Prepare for interviews
    Preparing for interviews is crucial to landing a job in data science. Make sure to research the company and the job description thoroughly, and practice answering common interview questions. You should also be prepared to demonstrate your skills by solving a problem or presenting a project you have worked on.
  • Keep learning
    The field of data science is constantly evolving, so it is essential to keep learning and updating your skills. Attend online courses, read blogs, and stay up to date with the latest technologies and tools.
  • Be open to opportunities
    As a fresher, you may not get your dream job right away. However, you can start by taking on smaller roles such as data analyst or data engineer to gain experience and build your skills. Be open to these opportunities and use them as a stepping stone to your ultimate goal.
  • Develop soft skills
    Soft skills, such as communication, teamwork, and problem-solving, are crucial for a data scientist. These skills help you work effectively with other professionals, present your findings, and solve complex problems. As a fresher, you can develop these skills by working on projects with other team members, attending workshops, and taking courses in communication and problem-solving.

Summing it Up

The industry is beginning to offer a world of opportunities to data science freshers. With data acquiring strategic importance in large, medium and small businesses, careers in data science are only going to get bigger. Organisations are looking to fill the ranks right from the entry level to the top level. If you aspire to become a sought-after data science talent, you need to acquire the right technical skills, sharpen your soft skills, build your portfolio and keep a tab on companies hiring data science talent.

We hope you found this blog helpful.

For more such blogs on career choices, tips, and information on building your careers, follow the NU blog.

Skip to content