Data science is one of the most exciting and rewarding fields in the world today. It involves using various tools and techniques to collect, analyze, and derive insights from large and complex data sets. Data science can help solve various problems and challenges in various domains such as business, healthcare, education, social media, etc.

A data scientist is a professional who applies data science skills and knowledge to create value for organizations and society. A data scientist can perform various tasks such as data collection, data cleaning, data exploration, data visualization, data modeling, data testing, data interpretation, and data communication.

Data science is a rapidly growing field in India, as more and more businesses are realizing the potential of data-driven decision making. According to a report by The Hindu, there are an estimated 97,000 data analytics job openings in India, with Bengaluru accounting for 24% of them. The demand for data scientists is expected to increase further in the coming years, as India generates more data than ever before.

If you are interested in becoming a data scientist in India, this article is for you. In this article, we will cover:

• Why choose data science as a career in India
• Educational requirements for becoming a data scientist
• Essential skills for a data scientist
• Key steps to becoming a data scientist in India
• Best institutions to pursue data science in India
• The role of online courses and certifications
• Tips for landing your first job as a data scientist
• Continuing education and skill development in data science

Why Choose Data Science as a Career in India

There are many reasons why you should consider choosing data science as a career in India. Some of them are:

• The surge in data generation in India: India is one of the largest producers and consumers of data in the world. According to a report by IDC, India’s digital economy will generate 2.3 zettabytes of data by 2020, which is equivalent to 2.3 trillion gigabytes. This massive amount of data offers immense opportunities for data scientists to extract valuable insights and create innovative solutions.
• Increasing demand for data scientists: As the amount of data increases, so does the need for skilled professionals who can analyze and interpret it. Data scientists are among the most sought-after roles in India, as they can help businesses gain a competitive edge, improve customer satisfaction, optimize operations, reduce costs, increase revenues, and drive innovation. According to Glassdoor, “data scientist” is one of the top 10 best jobs in India, with an average salary of Rs. 10 lakhs per annum.
• High salary prospects and career growth: Data science is one of the highest paying fields in India, as well as globally. According to PayScale, the average salary of a data scientist in India is Rs. 7 lakhs per annum, which can go up to Rs. 20 lakhs per annum for experienced candidates. Data scientists also have great career growth opportunities, as they can advance to senior roles such as lead data scientist, chief data officer, director of analytics, etc.
• Influential companies that hire data scientists in India: Data science is not limited to any specific industry or sector. It is applicable across various domains such as technology, finance, e-commerce, healthcare, education, entertainment, etc. Some of the influential companies that hire data scientists in India are Amazon, Flipkart, Google, Microsoft, Facebook, IBM, Accenture, Infosys, TCS, Wipro, etc.

Educational Requirements for Becoming a Data Scientist

To become a data scientist in India, you need to have a strong educational background in the relevant fields. Here are some of the educational requirements for becoming a data scientist:

• A basic degree in IT, computer science, math, physics, or related fields: To start your data science journey, you need to have a bachelor’s degree in a field that involves quantitative and analytical skills. You can opt for a B.Tech, B.Sc, BCA, or B.Stat degree in IT, computer science, math, physics, statistics, or any other related field. This will help you gain a foundational knowledge of programming, data structures, algorithms, databases, etc.
• Importance of a Master’s degree or a Ph.D. in the field: While a bachelor’s degree can help you enter the data science field, it may not be enough to advance your career. To become a more competent and credible data scientist, you may need to pursue a higher degree such as a Master’s or a Ph.D. in data science or related fields. This will help you gain more depth and breadth of knowledge and skills in data science, as well as specialize in a particular domain or area of interest. You can opt for an M.Tech, M.Sc, MCA, M.Stat, or Ph.D. degree in data science, computer science, statistics, machine learning, artificial intelligence, etc.
• Importance of specialized data science programs and certifications: Apart from the formal degrees, you may also need to enroll in specialized data science programs and certifications that can help you learn the latest tools and techniques in the field. These programs and certifications can help you bridge the gap between theory and practice and enhance your employability and credibility. You can opt for online or offline courses and certifications offered by various institutions and platforms such as Coursera, EdX, Udemy, etc.

Essential Skills for a Data Scientist

To become a successful data scientist in India, you need to have a combination of technical and non-technical skills. Some of the essential skills for a data scientist are:

• Technical skills: These are the skills that involve using various tools and technologies to perform data science tasks. Some of the technical skills that you need to master are:
  • Python/R: These are the most popular programming languages for data science, as they offer various libraries and packages for data manipulation, analysis, visualization, and modeling. You need to be proficient in writing code using Python or R to perform various data science operations.
  • SQL: SQL stands for Structured Query Language and it is used to interact with relational databases. You need to be able to write SQL queries to extract, filter, join, aggregate, and manipulate data from various sources.
  • Machine Learning: Machine learning is the core of data science, as it involves creating algorithms and models that can learn from data and make predictions or decisions. You need to be familiar with various machine learning concepts such as supervised learning, unsupervised learning, classification, regression, clustering, etc. You also need to be able to use various machine learning frameworks and tools such as scikit-learn, TensorFlow, PyTorch, etc.
  • Data Visualization and Reporting: Data visualization and reporting are the skills that involve presenting and communicating the results and insights derived from data analysis. You need to be able to use various data visualization tools such as Matplotlib, Seaborn, Plotly, Tableau, Power BI, etc. to create charts, graphs, dashboards, etc. You also need to be able to write clear and concise reports that explain the findings and recommendations from your data science projects.
• Statistics and mathematical skills: These are the skills that involve using various statistical and mathematical concepts and techniques to understand and analyze data. Some of the statistics and mathematical skills that you need to master are:
  • Descriptive statistics: Descriptive statistics are used to summarize and describe the basic features of a data set such as mean, median, mode, standard deviation, range, frequency, etc. You need to be able to calculate and interpret these measures to get a sense of the data distribution and variability.
  • Inferential statistics: Inferential statistics are used to draw conclusions and make inferences about a population based on a sample of data. You need to be able to use various inferential techniques such as hypothesis testing, confidence intervals, correlation, regression, ANOVA, chi-square, etc. to test your assumptions and hypotheses and measure the relationships and differences among variables.
  • Probability: Probability is the measure of the likelihood of an event or outcome occurring. You need to be able to use various probability concepts and rules such as conditional probability, Bayes’ theorem, probability distributions, etc. to model and estimate the uncertainty and randomness in data.
  • Linear algebra: Linear algebra is the branch of mathematics that deals with vectors, matrices, and linear equations. You need to be able to use various linear algebra operations such as matrix multiplication, inverse, transpose, determinant, eigenvalues, eigenvectors, etc. to perform various data transformations and manipulations.
  • Calculus: Calculus is the branch of mathematics that deals with functions, limits, derivatives, integrals, and optimization. You need to be able to use various calculus concepts and techniques such as differentiation, integration, gradient descent, etc. to optimize and evaluate various functions and models in data science.
• Domain knowledge and understanding of business strategies: These are the skills that involve having a deep understanding of the domain or industry that you are working in and the business goals and strategies that you are trying to achieve. You need to be able to:
  • Identify the business problem or opportunity that can be solved or explored using data science.
  • Define the scope and objectives of the data science project and align them with the business goals and expectations.
  • Collect and analyze relevant data from various sources that can help answer the business question or hypothesis.
  • Choose and apply appropriate data science methods and techniques that can provide optimal solutions or insights for the business problem or opportunity.
  • Communicate and present the results and recommendations from the data science project to the stakeholders and decision-makers in a clear and convincing manner.
• Soft skills: These are the skills that involve your personal attributes and interpersonal abilities that can help you work effectively in a team and with others. Some of the soft skills that you need to develop are:
  • Communication: Communication is the skill of expressing your ideas, thoughts, opinions, feedback, etc. in a clear and concise manner using various modes such as verbal, written, visual, etc. You need to be able to communicate effectively with your team members, managers, clients, etc. using appropriate language, tone, style, etc. You also need to be able to listen actively and attentively to others and respond appropriately.
  • Teamwork: Teamwork is the skill of working collaboratively with others towards a common goal or purpose. You need to be able to cooperate with your team members, share your knowledge and skills, respect their opinions and perspectives, give and receive constructive feedback, and resolve any conflicts or issues that may arise.
  • Problem-solving: Problem-solving is the skill of identifying, analyzing, and solving various problems or challenges that you may encounter in your data science projects. You need to be able to use various problem-solving techniques such as brainstorming, root cause analysis, trial and error, etc. to find the best possible solutions or alternatives. You also need to be able to think creatively and critically and apply logical reasoning and common sense.
  • Adaptability: Adaptability is the skill of adjusting and coping with changing situations and environments. You need to be able to learn new skills and technologies quickly and effectively, as data science is a dynamic and evolving field. You also need to be able to handle uncertainty and ambiguity and deal with stress and pressure.

Key Steps to Becoming a Data Scientist in India

To become a data scientist in India, you need to follow these key steps:

• Gaining a strong foundational knowledge: The first step is to gain a strong foundational knowledge of the core concepts and principles of data science, such as programming, statistics, mathematics, machine learning, etc. You can do this by pursuing a relevant bachelor’s degree in IT, computer science, math, physics, or related fields. You can also supplement your learning by taking online courses and certifications that can help you learn the basics of data science.
• Pursuing relevant degrees/certifications: The next step is to pursue relevant degrees or certifications that can help you gain more advanced and specialized knowledge and skills in data science. You can do this by pursuing a master’s degree or a Ph.D. in data science or related fields. You can also opt for specialized data science programs and certifications offered by various institutions and platforms that can help you learn the latest tools and techniques in the field.
• Gaining practical experience through projects/internships: The third step is to gain practical experience through projects and internships that can help you apply your data science skills and knowledge to real-world problems and scenarios. You can do this by working on various data science projects that interest you or are relevant to your domain or industry. You can also look for internships or part-time jobs that can help you gain exposure to the data science work environment and culture.
• Networking with professionals in the field: The fourth step is to network with professionals in the field who can help you learn from their experiences, insights, and advice. You can do this by attending various data science events, meetups, workshops, webinars, etc. that are organized by various communities and organizations. You can also join various online forums, groups, platforms, etc. where you can interact with other data scientists and enthusiasts.
• Continual learning to stay updated with the latest tools and technologies: The final step is to keep learning new skills and technologies that are emerging in the field of data science. Data science is a fast-paced and ever-changing field that requires you to stay updated with the latest trends and developments. You can do this by reading various blogs, articles, books, journals, etc. that cover the latest topics and research in data science. You can also enroll in various online courses and certifications that can help you learn new tools and techniques in the field.

Best Institutions to Pursue Data Science in India

There are various institutions in India that offer data science courses and programs at different levels. Some of the best institutions to pursue data science in India are:

• Indian Institute of Technology (IIT): IIT is one of the most prestigious and reputed institutions in India that offers various courses and programs in data science and related fields. Some of the courses and programs offered by IIT are:
  • B.Tech in Computer Science and Engineering with specialization in Data Science
  • M.Tech in Data Science
  • Ph.D. in Data Science
  • Certificate Program in Data Science and Machine Learning
  • Executive Program in Data Science
• Indian Institute of Management (IIM): IIM is one of the most renowned and respected institutions in India that offers various courses and programs in data science and related fields. Some of the courses and programs offered by IIM are:
  • Post Graduate Diploma in Business Analytics (PGDBA)
  • Post Graduate Program in Data Science, Business Analytics, and Big Data (PGP-DSBA)
  • Executive Program in Advanced Business Analytics (EPABA)
  • Certificate Program in Business Analytics for Executives (CPBAE)
• Indian Statistical Institute (ISI): ISI is one of the oldest and most distinguished institutions in India that offers various courses and programs in data science and related fields. Some of the courses and programs offered by ISI are:
  • B.Stat (Hons.) with specialization in Data Science
  • M.Stat with specialization in Data Science
  • M.Tech in Computer Science with specialization in Machine Learning
  • Ph.D. in Computer Science with specialization in Machine Learning
  • Post Graduate Diploma in Statistical Methods and Analytics
• International Institute of Information Technology (IIIT): IIIT is one of the leading institutions in India that offers various courses and programs in data science and related fields. Some of the courses and programs offered by IIIT are:
  • B.Tech in Computer Science and Engineering with specialization in Data Engineering
  • M.Tech in Computer Science and Engineering with specialization in Data Engineering
  • M.Tech in Computer Science and Engineering with specialization in Artificial Intelligence
  • Ph.D. in Computer Science and Engineering with specialization in Artificial Intelligence
  • Post Graduate Certificate Program in Data Science
• National Institute of Technology (NIT): NIT is one of the premier institutions in India that offers various courses and programs in data science and related fields. Some of the courses and programs offered by NIT are:
  • B.Tech/M.Tech Dual Degree Program in Computer Science and Engineering with specialization in Data Analytics
  • M.Tech/M.Sc Dual Degree Program in Mathematics/Statistics/Operations Research with specialization in Data Science
  • Ph.D. in Computer Science and Engineering with specialization in Data Science
  • Ph.D. in Mathematics/Statistics/Operations Research with specialization in Data Science
  • Certificate Course in Data Science

The Role of Online Courses and Certifications

Online courses and certifications play an important role in learning and enhancing your data science skills and knowledge. Online courses and certifications can help you:

• Learn the basics and fundamentals of data science at your own pace and convenience.
• Gain access to high-quality content and resources from experts and instructors from various institutions and organizations.
• Gain hands-on experience and practice through various assignments, projects, quizzes, etc.
• Earn a credential or a certificate that can showcase your skills and knowledge to potential employers and clients.
• Stay updated with the latest tools and techniques in the field of data science.

Some of the best online platforms that offer data science courses and certifications are:

• Coursera: Coursera is one of the most popular and widely used online platforms that offers various courses and programs in data science and related fields. Some of the best data science courses and programs offered by Coursera are:
  • IBM Data Science Professional Certificate
  • Applied Data Science with Python Specialization
  • Data Science Specialization by Johns Hopkins University
  • Machine Learning by Stanford University
  • Deep Learning Specialization by deeplearning.ai
• EdX: EdX is another leading online platform that offers various courses and programs in data science and related fields. Some of the best data science courses and programs offered by EdX are:
  • Microsoft Professional Program in Data Science
  • HarvardX’s Data Science Professional Certificate
  • MITx’s MicroMasters Program in Statistics and Data Science
  • UC San DiegoX’s MicroMasters Program in Data Science
  • BerkeleyX’s Professional Certificate in Foundations of Data Science
• Udemy: Udemy is another popular online platform that offers various courses and programs in data science and related fields. Some of the best data science courses and programs offered by Udemy are:
  • The Data Science Course 2020: Complete Data Science Bootcamp
  • Machine Learning A-Z: Hands-On Python & R In Data Science
  • Python for Data Science and Machine Learning Bootcamp
  • Data Science and Machine Learning Bootcamp with R
  • Tableau 2020 A-Z: Hands-On Tableau Training for Data Science

Tips for Landing Your First Job as a Data Scientist

Landing your first job as a data scientist can be challenging, as you may face competition from other candidates who may have more experience or qualifications than you. However, you can increase your chances of getting hired by following these tips:

• Preparing a strong resume and portfolio: Your resume and portfolio are the first impressions that you make on your potential employer. You need to make sure that they highlight your skills, knowledge, education, projects, certifications, etc. in a clear and concise manner. You also need to tailor your resume and portfolio according to the job description and requirements of the company that you are applying to.
• Practicing data science problems and participating in data science competitions: Practicing data science problems can help you improve your problem-solving skills, as well as test your knowledge and understanding of various data science concepts and techniques. Participating in data science competitions can help you showcase your skills, as well as gain exposure to real-world problems and scenarios. You can find various data science problems and competitions on platforms such as Kaggle, HackerRank, CodeChef, etc.
• Preparing for data science interviews: Data science interviews can be challenging, as they may involve various types of questions such as technical, behavioral, case study, etc. You need to prepare well for each type of question by reviewing your concepts, revising your projects, researching the company, etc. You also need to practice your communication skills, as well as demonstrate your enthusiasm and passion for data science.
• Leveraging LinkedIn and other job portals: LinkedIn is one of the most powerful tools for finding data science jobs, as it allows you to connect with professionals, recruiters, companies, etc. in the field. You need to create a professional profile on LinkedIn that showcases your skills, education, experience, projects, certifications, etc. You also need to network with other data scientists, join relevant groups, follow influential pages, etc. You can also use other job portals such as Indeed, Naukri.com, Monster.com, etc. to search and apply for data science jobs.

Continuing Education and Skill Development in Data Science

Data science is a dynamic and evolving field that requires you to keep learning new skills and technologies to stay relevant and competitive. You need to adopt a lifelong learning attitude and pursue various opportunities for continuing education and skill development in data science. Some of the ways you can do this are:

• Platforms for continued learning and staying updated: There are various online platforms that offer various courses and programs for continued learning and staying updated in data science. Some of the best platforms are:
  • Coursera: Coursera offers various courses and programs for advanced and specialized topics in data science such as Natural Language Processing, Computer Vision, Deep Reinforcement Learning, etc.
  • EdX: EdX offers various courses and programs for advanced and specialized topics in data science such as Big Data Analytics, Artificial Intelligence, Blockchain Technology, etc.
  • Udemy: Udemy offers various courses and programs for advanced and specialized topics in data science such as Spark and Scala, TensorFlow 2.0, PyTorch, etc.
• Blogs, articles, books, journals, etc.: Reading various blogs, articles, books, journals, etc. can help you learn from the experiences, insights, and advice of experts and practitioners in the field of data science. Some of the best sources are:
  • Towards Data Science: Towards Data Science is a popular online publication that covers various topics and trends in data science such as machine learning, artificial intelligence, data visualization, etc.
  • Analytics Vidhya: Analytics Vidhya is a leading online platform that provides various resources and content for learning and practicing data science such as articles, courses, hackathons, webinars, etc.
  • Data Science Central: Data Science Central is a comprehensive online resource for data science professionals that offers various content such as blogs, podcasts, webinars, ebooks, newsletters, etc.
  • Introduction to Statistical Learning: Introduction to Statistical Learning is a classic book that provides an accessible introduction to the core concepts and techniques of statistical learning and machine learning.
  • Pattern Recognition and Machine Learning: Pattern Recognition and Machine Learning is a comprehensive book that covers various topics and methods of pattern recognition and machine learning such as Bayesian inference, linear models, neural networks, kernel methods, graphical models, etc.
  • Journal of Machine Learning Research: Journal of Machine Learning Research is a peer-reviewed online journal that publishes high-quality research papers on various aspects of machine learning such as theory, algorithms, applications, etc.
• Events, meetups, workshops, webinars, etc.: Attending various events, meetups, workshops, webinars, etc. can help you network with other data scientists, learn from their presentations and discussions, and stay updated with the latest developments and innovations in the field of data science. Some of the best events are:
  • DataHack Summit: DataHack Summit is an annual conference organized by Analytics Vidhya that brings together data science enthusiasts, experts, and leaders from various domains and industries to share their knowledge and insights on data science.
  • Machine Learning India: Machine Learning India is a community of machine learning enthusiasts and practitioners that organizes various events and activities such as meetups, workshops, hackathons, etc. to promote and foster machine learning in India.
  • PyData: PyData is a global community of data science enthusiasts and practitioners that use Python and other open-source tools for data analysis and visualization. PyData organizes various events such as conferences, meetups, workshops, etc. to share best practices and learn from each other.

Last Words!

Data science is a promising and rewarding career that offers various opportunities and challenges for data enthusiasts and professionals in India. To become a data scientist in India, you need to follow the steps outlined in this article:

• Gain a strong foundational knowledge of data science.
• Pursue relevant degrees or certifications in data science.
• Gain practical experience through projects or internships.
• Network with professionals in the field.
• Continual learning to stay updated with the latest tools and technologies.

If you have the passion and the determination to become a data scientist in India, go for it and make it happen. The world of data awaits you.