How to Become a Data Scientist in India?

Data science has quickly become one of the most sought-after careers in the world, and India is no exception. With its booming tech industry and the abundance of data-driven opportunities, pursuing a career as a data scientist in India can be a rewarding choice. This comprehensive guide will walk you through everything you need to know on how to become a data scientist in India, from understanding the role of a data scientist to gaining practical experience and navigating the job market.

Who is a Data Scientist?

A data scientist is an individual who possesses a unique blend of technical skills, domain knowledge, and business acumen. They are responsible for collecting, analyzing, and interpreting large volumes of data to uncover meaningful patterns and trends. Data scientists use various programming languages and statistical methods to turn raw data into actionable insights.

What Does a Data Scientist Do?

Data scientists play an important role in extracting insights from data to inform strategic decisions. They gather and preprocess data, collaborate with stakeholders to define objectives and apply machine learning and statistical analysis to uncover trends and predictions. Utilizing programming languages like Python and R, along with tools like Jupyter Notebooks and Pandas, they conduct exploratory data analysis, create visualizations, and communicate findings to guide business strategies, ensuring continuous learning and staying abreast of industry advancements.

Why Choose a Data Science Career in India?

A Career in data science is booming in India! Driven by a data-centric environment and large supportive network, this field offers exciting opportunities, competitive salaries, and a clear path to success. Let’s dive deeper into the factors driving this growth –

1. Data Boom & Growing Demand in India

India’s data science industry is experiencing significant growth, thanks to the increasing adoption of data-driven decision-making practices by organizations. The data science education market in India is expected to grow at a CAGR of 57.52% from $204.23 million in 2023 to $1.39 billion by 2028.

2. Tech Hub & Lucrative Salaries

Furthermore, India is home to several tech hubs and multinational companies that offer diverse data science job opportunities. The demand for skilled data scientists is high, and the salaries are competitive. This makes pursuing a career in data science in India an attractive option for aspiring professionals. According to Glassdoor, the average salary for a Data Scientist is ₹12,60,276 per year in India, with a range from ₹8L – ₹20L/yr.

3. Strong Talent Pool

India is becoming a hotspot for data science careers! This is because of the country’s large pool of talented professionals with strong technical skills. With a robust education system producing a high number of engineering and computer science graduates each year, India has a rich talent pool that is well-equipped to handle the demands of the data science industry.

4. Government Support

The Indian government has been actively promoting initiatives to support the growth of the data science sector. Programs such as Skill India and Digital India aim to enhance the skills of the workforce and drive digital transformation, creating a conducive environment for data science professionals to thrive.

Education and Certifications Needed to Become a Data Scientist in India

While there is no strict educational requirement to become a data scientist in India, having a strong foundation in mathematics, statistics, and computer science is essential. Let’s explore the educational pathways that lead to success in this exciting field.

Bachelor’s Degree

Many data scientists hold graduate or postgraduate degrees in fields like computer science, statistics, mathematics, or even engineering (especially IT-related) providing a solid base. This ensures a solid grounding in core data science concepts. Here’s a list of top Data Science colleges in India known for their strong data science undergraduate programs that you can consider- 

• Indian Institute of Technology (IITs) like IIT Madras, IIT Bombay, IIT Delhi, IIT Kanpur (Consider entrance exams like JEE Mains/Advanced)
• International Institute of Information Technology (IIITs) like IIIT Hyderabad and IIIT Bangalore
• Indian Institute of Science (IISc), Bangalore
• Loyola College, Chennai
• BITS Pilani

Remember to research costs (scholarships might be available!) and entrance exams (if applicable) for each program. Ultimately, the “best” bachelor’s degree depends on your strengths, interests, and learning style. Research several programs, speak with current students or alumni, and select the path that aligns best with your goals.

Specialized Courses & Certifications

Certification programs and specialized courses in data science like the Scaler Data Science course can provide you with the necessary skills and knowledge to excel in this field. Popular certifications include those offered by leading organizations like IBM, Microsoft, and SAS. Here are a few Data Science certifications that you can consider- 

• Google Professional Data Engineer 
• AWS Certified Data Analytics Specialty 
• SAS (Statistical Analysis System) Certified Data Scientist 
• Certified Analytics Professional (CAP)
• Cloudera Certified Associate (CCA) Data Analyst 
• Microsoft Certified 

Earning certifications showcase your proficiency and keep your skills current with the latest advancements in data science. It can also enhance your resume and help you stand out to potential employers. Carefully research your options to find the best fit for your learning goals and budget.

While certifications are not absolutely required to apply for a data science job, they can provide you with the knowledge and skills to succeed in a data science role.

Hands-on experience

Hands-on experience is very important for solidifying your theoretical knowledge and becoming a proficient data scientist. Here are various ways to gain practical experience:

• Internships: Look for opportunities in data science or related fields like machine learning, artificial intelligence, or business analytics. Look for internship opportunities on job boards, university career portals, or directly contacting companies you’re interested in.
• Personal Projects: Find publicly available datasets online (e.g., government websites, UCI Machine Learning Repository, Kaggle) and work on your own projects. This allows you to explore areas that interest you and build a portfolio showcasing your skills.
• Open-Source Contributions:  Contribute to open-source data science projects on platforms like GitHub. This provides valuable learning experiences as well as the chance to work with experienced data scientists.
• Competition Platforms:  Participating in data science competitions like Kaggle and Machine Hack allows you to test your skills against other aspiring data scientists, learn from different approaches, and improve your problem-solving abilities in a competitive environment.

To help you get started, we have mentioned some data science project ideas for you. Every project provides an opportunity to practice and acquire new skills. Here’s the list- 

• Fake News Detection Using Python
• Sentimental Analysis

• Speech Recognition through Emotions
• Detection of Drowsiness in Drivers
• Gender Detection and Age Prediction 
• Detection of Credit Card Fraud
• Customer Segmentations
• Developing Chatbots
• Detection of Road Lane Lines 
• Recognition of traffic signals
• Recommendation System for Films

Bootcamps

For those looking for a quicker path to entering into the data science field, data science bootcamps can be a great alternative. These programs typically last three to six months and equip you with essential data science skills and knowledge. Before choosing the right data science boot camp for you, consider the following points- 

• You career goal
• Assess your current skills
• Research the program thoroughly
• Consider location and structure (online, in-person, or hybrid program.)
• What topics are covered
• Carefully research costs and financing options.
• Research institution reputation

There are various data science boot camp options to choose from. Here’s a list of top data science boot camps to help you get started – 

• General Assembly
• Springboard

Master’s Degree

While not mandatory, aspiring data science leaders can pursue a master’s degree to gain advanced knowledge and qualify for managerial positions. Having a master’s degree with a focus on data science, statistics, or a related field can give you advanced knowledge and skills, and a faster path to leadership roles. This can give you a competitive edge in the current job market. Here’s the list of top colleges in India for a master’s degree in data science or a related field:

• Indian Institute of Technology (IITs) like IIT Madras, IIT Bombay, IIT Delhi, IIT Kanpur (Consider entrance exams like JEE Mains/Advanced)
• International Institute of Information Technology (IIITs) like IIIT Hyderabad and IIIT Bangalore
• Indian Institute of Science (IISc), Bangalore
• National Institute of Technology (NIT) Tiruchirappalli
• BITS Pilani

Essential Skills You Need to Become a Data Scientist in India

Although having a solid educational foundation is important, data science requires a combination of technical and non-technical skills. To thrive as a data scientist in India, you’ll need a combination of technical and soft skills. Here are some essential skills you need to become a data scientist in India- 

Technical Skills 

• Programming languages such as Python, R, and Scala.
• Strong understanding of statistics and maths
• Data manipulation tools like pandas, NumPy
• Data visualization tools such as Tableau, Power BI
• Understanding databases and querying languages like SQL 
• AI and machine learning
• Deep learning
• Natural language processing
• Big data skills

Non-Technical Skills 

• Critical thinking 
• Problem-solving 
• Business Acumen
• Management Skills
• Effective communication and storytelling abilities 
• Continuous learning and upskilling 
• Networking with professionals

Tips to Gaining Practical Experience

While academic qualifications are important, practical experience is equally valuable for aspiring data scientists. Here are some tips to gain practical experience:

1. Participate in data science competitions and hackathons to solve real-world problems.
2. Contribute to open-source projects and collaborate with experienced professionals.
3. Start your own data science projects to explore different techniques and showcase your skills.
4. Intern or work on data-related projects to gain hands-on experience.

Engaging in data science competitions and hackathons not only allows you to apply your theoretical knowledge to real-world scenarios but also helps you sharpen your problem-solving skills under pressure. These events often provide datasets with complex challenges that require innovative solutions, giving you a chance to think creatively and collaborate with like-minded individuals.

Furthermore, contributing to open-source projects is a fantastic way to immerse yourself in the data science community. By working alongside experienced professionals, you can learn best practices, receive valuable feedback on your code, and build a network of contacts that may lead to future opportunities. Open-source projects cover a wide range of topics, allowing you to explore different areas of interest within data science and gain exposure to diverse techniques and tools.

Courses Needed to Become a Data Scientist in India

There are numerous online and offline courses available to help you kickstart your journey as a data scientist in India. Some popular courses include the Scaler Data Science Course which equips you with the essential skills needed to become an expert data scientist such as: 

• Introduction to Data Science
• Machine Learning
• Deep Learning
• Data Visualization
• Big Data Analytics

This course provides a comprehensive foundation in data science concepts, tools, and techniques. They often include assignments, emphasize hands-on learning with real-world projects to further enhance your practical skills, and provide 1:1 mentorship from industry experts. They often include assignments and projects to further enhance your practical skills. 

Moreover, in addition to these core courses, it is highly recommended for aspiring data scientists to also delve into specialized topics such as Natural Language Processing (NLP), Time Series Analysis, and Reinforcement Learning. These areas of study are crucial for understanding advanced machine learning algorithms and expanding your expertise in specific domains.

Furthermore, to excel in the field of data science, it is essential to continuously update your skills and stay abreast of the latest industry trends. This can be achieved by participating in workshops, attending conferences, and joining online communities dedicated to data science.

How to Build an ATS-Friendly Data Scientist Resume

When applying for data scientist roles, it’s crucial to optimize your resume for Applicant Tracking Systems (ATS). Here are some tips:

• Identify relevant keywords and skills mentioned in Indian data science job descriptions (e.g., Python, SQL, Machine Learning, Spark, Big Data). Use these keywords throughout your resume, especially in your job description, summary, skills section, and project. 
• Don’t rely on a one-size-fits-all approach. Tailor your resume for each position by highlighting the skills and experiences that are most relevant to the specific job requirements.
• Highlight your technical skills including programming languages (Python, R, SQL), data analysis tools (Pandas, NumPy, Tableau), and machine learning libraries (Scikit-learn, TensorFlow). Also, soft skills like communication, teamwork, problem-solving, and analytical thinking abilities are relevant to data science roles.
• Use metrics and quantifiable results wherever possible to show the impact of your work on previous projects. 
• Showcase your data science projects, highlighting the problem solved, techniques you have used, and the results achieved. Include links to relevant code repositories on platforms like Github if applicable.
• Include any data science-related certifications you’ve obtained (e.g., AWS Certified Solutions Architect, Google Cloud Professional Data Engineer).
• Ensure your resume is well-structured, concise, and error-free.

Data Science Resume Sample

Here is a data science resume sample specifically for an entry-level data scientist position in India. This template covers the career objective, skills, internships, project details, talents, and related courses taken in college.

There are many Data Scientist resume templates available online, both free and paid. We’ve also compiled a list of websites where you may download a suitable Data Scientist resume template based on your experience or role. Here’s the list-

• Enhancv
• Google Doc
• Zety
• Beamjobs

How to Get a Job Data Science Job in India?

The data science job market in India is expanding, but with so many aspiring data scientists, competition can be tough.

Searching for a job as a data scientist in India can be an overwhelming process. Here are some strategies to navigate the job market effectively:

1. Build a strong online presence by showcasing your skills and projects on platforms like LinkedIn and GitHub.
2. Network with professionals in the field through industry events, conferences, and online communities.
3. Apply to data science job portals and platforms specifically designed for data science professionals.
4. Prepare for technical interviews by practicing coding, machine learning algorithms, and data analysis.

Furthermore, it’s essential to tailor your resume and cover letter to each job application, highlighting relevant experience and skills that match the job requirements. Personalizing your application materials can significantly increase your chances of getting noticed by recruiters and hiring managers. Additionally, consider seeking out mentorship opportunities or joining mentorship programs to gain insights and guidance from experienced professionals in the data science industry.

When attending networking events or industry conferences, make sure to engage in meaningful conversations with fellow professionals and recruiters. Building genuine connections can open up new opportunities and provide valuable insights into the current job market trends and demands. It’s also beneficial to stay updated on the latest developments in the data science field by following industry blogs, attending webinars, and participating in online courses to enhance your skills and knowledge.

Continuous Learning and Community Engagement

Data science is a rapidly evolving field, with new tools, techniques, and methodologies constantly being developed. Staying abreast of these advancements is essential to remain competitive and relevant in the industry. Continuous learning through online courses, workshops, and self-study is a proactive way to enhance your skills and knowledge.

Engaging with the data science community offers a wealth of benefits beyond just staying informed. By actively participating in online forums, discussion groups, and social media platforms dedicated to data science, you can tap into a vast network of professionals with diverse backgrounds and experiences. 

Here are some additional resources to jumpstart your exploration:

• Forums:
  • Stackexchange.com: A question-and-answer forum with a wealth of information on various data science topics.
  • Reddit.com/MachineLearning: The Machine Learning subreddit on Reddit, offers discussions, project showcases, and career advice.

• Communities:
  • Datasciencecentral.com: Data Science Central, a comprehensive platform with articles, tutorials, and webinars on data science and machine learning.
  • Datasciencesociety.net: The Data Science Society, a global organization promoting data science education and collaboration.

Data Scientist Job Outlook in India

The job outlook for data scientists in India is promising. Here are some stats showing the rising demand for this highly sought-after job-  

•  According to the U.S. Bureau of Labor Statistics, the employment of data scientists is projected to grow by 35% from 2022 to 2032, resulting in approximately 17,700  new job openings. 
• According to Forbes, data science and analytics is one of the fastest-growing jobs of 2024. It has a projected growth rate of 26% from 2021 to 2031.
• According to a report by Analytics India Magazine, the analytics industry in India reached $3.03 billion (in size) in 2019 and is expected to double by 2025. 

Additionally, industries such as e-commerce, healthcare, finance, and technology are the major adopters of data science in India. These industries offer a wide range of opportunities for data scientists to work on meaningful projects and make a significant impact. Since there is a need for qualified data scientists in all of these businesses, now is the perfect time for aspiring professionals to enter the industry.

Furthermore, the government’s initiatives such as Digital India and Smart Cities Mission have created a conducive environment for the growth of data science in the country. These initiatives have generated vast amounts of data that need to be analyzed to improve governance, infrastructure, and public services. As a result, data scientists play a crucial role in helping government bodies make informed decisions based on data-driven insights.

Data Scientist Salary in India

In India, the median annual salary of a data scientist is around ₹8-20 lakhs, depending on experience and expertise. However, top-tier organizations and professionals with advanced skills can earn upwards of ₹50 lakhs per annum.

It’s important to note that the demand for data scientists in India has been steadily increasing due to the rapid digital transformation across industries. This surge in demand has led to a competitive job market where companies are willing to offer attractive salary packages to skilled data scientists. Additionally, the rise of data-driven decision-making in businesses has further elevated the importance of data scientists, leading to higher salaries being offered to retain top talent.

Furthermore, the location within India can also impact the salary of a data scientist. For instance, metropolitan cities like Bangalore, Mumbai, and Delhi NCR tend to offer higher salaries compared to tier-2 cities. According to Glassdoor, the average salary for a data scientist is ₹13,75,000 in Bangalore and ₹12,92,000 in New Delhi. 

This is often attributed to the cost of living in these metropolitan areas, as well as the concentration of tech companies and startups that require data science expertise. As the field of data science continues to evolve and expand, it is expected that salaries for data scientists in India will also see a corresponding increase in the coming years.

Conclusion

Pursuing a career as a data scientist in India offers immense opportunities and rewards. With the right skills, education, and practical experience, you can embark on a successful journey in this exciting field. Stay committed to continuous learning, engage with the data science community, and navigate the job market strategically. By following this ultimate guide, you’ll be well on your way to building a thriving career as a data scientist in India.

Frequently Asked Questions