Technological advancements have unlocked the doorway to the digital world. To stay relevant, companies across sectors create a digital presence. They want to connect with customers through searches, swipes and clicks.
Whenever a person performs such activities, it generates an ocean of data. To bridge the gap between raw information and actionable insights and help companies make decisions, a concept emerges. That is data science.
It combines techniques from computer science, statistics, machine learning and domain-specific knowledge to extract meanings and patterns from data.
In the current business market, data science is a buzzword for good reasons. It is a significant step forward in how computers can learn and use data to drive business decisions. Since data-driven decisions are essential across all sectors, there is a high demand for data science professionals.
After 12th, students who want to be part of the data-driven world can choose careers in Data Science. Through various data science courses, you can learn about the latest trends like Artificial Intelligence, Machine Learning and Big Data.
As these trends shape the operations of different businesses, careers in data science are also advantageous. Not to mention, job roles such as Data Scientist, Data Analyst, Data Architect, and others offer lucrative salary packages.
But what is the scope of data science? Well, this blog will give you a detailed answer to the question. Furthermore, it will inform you about the different career options across sectors and salary packages.
Key Takeaways
- Companies like Google and Facebook began applying data science principles in the early 2000s to extract data to improve customer service. The domain combines statistics, computer science and mathematics to conduct data analysis.
- Artificial Intelligence, Machine Learning, and the Internet of Things (IoT) are popular trends that expand the scope of data science. Industries such as Retail, Manufacturing, and Healthcare utilise these trends to make better decisions and enhance operational efficiency.
- The demand for data science professionals in the Indian education market is increasing, and it is projected to reach USD 2.04 billion by 2028. Additionally, data science holds a promising future in countries such as the USA, Germany, and Australia.
- Skills in Python, R, Hadoop and AWS unlock vast career opportunities as Data Analysts, Data Scientists and Machine Learning Engineers.
- B.Sc/B. Tech graduates in Data Science can earn INR 5 LPA – INR 8 LPA across all sectors. As you gain more skills, the senior-level positions can offer INR 35 LPA and beyond.
What is Data Science? A Brief Overview
Businesses and organisations are heavily relying on data to make informed decisions. Such a scenario holds promise for data science. But what is data science?
It is an interdisciplinary field that uses machine learning, statistical analysis, and other tools to extract insights from large datasets. The field combines mathematics, computer science and statistics.
Using knowledge and skills from these domains, professionals collect, process and analyse data. The professionals are known as data scientists. With a myriad of tools and techniques, they make predictions or recommendations.
It was in the early 2000s that companies like Google and Facebook realised the potential of data science. These organisations use the discipline’s core principles to mine user data and improve their services. Since then, there has been a revolution in the scope of data science.
As we move forward, individuals are leveraging it across industries to inform business decisions.
Key Responsibilities of a Data Scientist
After 12th science, data science as a career option for students is quite promising. The constant demand for data analysis to support better business decisions has led to the rise of data science.
To conduct the analysis, companies require data scientists. They combine programming, statistics and domain expertise to create actionable data insights. In addition, data scientists have several key responsibilities. We’ll explore them one by one:
- One of the significant roles of data scientists is to create models and algorithms. They use these elements to make predictions or solve complex business problems.
- A core responsibility of data scientists is to present their findings clearly and concisely to others. These professionals should possess the skills to articulate technical concepts to both technical and non-technical people.
- It is the job of such professionals to collaborate with other teams. Data scientists help teams like product development and marketing utilise data patterns.
- Data scientists must stay current with the field’s latest developments and trends. To do so, they can read industry publications, attend conferences, and participate in training programs. As a result, it lays a foundation for the future scope of data science.
What Makes Data Science a Future-Proof Career?
Wondering what could be the best career options after 12th science? Well, engineering and medical remain popular options. But the rising demand for accurate predictions in businesses creates a way for data science.
The data science field is not tied to one domain. From healthcare to banking, every sector requires professionals who make sense of numbers. While banks use data insights to prevent fraud, healthcare uses them to predict patient risk.
Leveraging data insights can offer students in data science a well-rounded career objective. If you are also passionate about numbers, data science can offer you a prosperous career. Besides its applications in various sectors, the field provides a future-proof career:
- Data science provides advanced technical skills to solve complex business problems.
- The field offers high earning potential due to the difficulty of the job roles.
- Data science helps professionals to understand their customers better and improve operational efficiency.
- It lays the foundation for artificial intelligence and machine learning. As these are powerful market trends, demand for data scientists also increases. They build algorithms to automate organisations’ repetitive tasks.
Top Career Options in Data Science
People may wonder whether data science is a good career option. Well, it is an interdisciplinary field crucial to understanding complex datasets.
To break down complex datasets, businesses require professionals in this domain. The following table will provide the top career options in data science:
| Career Options | Responsibilities | Required Skills | Avg. Salary |
|---|---|---|---|
| Data Scientist | – Creating data models and algorithms – Showing clear and concise findings to technical and non-technical people – Collaborating with teams to make them understand data better | Programming, statistics, machine learning and data wrangling | INR 5 LPA- INR 25 LPA |
| Machine Learning Engineer | – Designing and building machine learning systems – Creating and implementing algorithms – Maintaining machine learning systems | Data handling, knowledge in big data and cloud computing and model deployment | INR 9.9 LPA- INR 11 LPA |
| Data Analyst | – Collecting and gathering data from various sources – Cleaning and organising data – Managing systems | Proficient in SQL, programming (Python, R, etc) and problem-solving skills | INR 3 LPA –INR 10 LPA |
| Data Architect | – Creating conceptual and logical data models – Ensuring data quality – Creating data strategy | Data modelling, cloud computing, machine learning and data mining & analysis | INR 6 LPA- INR 20 LPA |
| Business Intelligence Analyst | – Collecting and gathering data for analysis – Creating reports and dashboards – Identifying trends and collaborating with stakeholders | Using data visualisation tools, proficient in programming languages and skills to understand statistical software | INR 6.1 LPA- INR 7.5 LPA |
Scope of Data Science in Different Industries
Whenever someone says ‘data science,’ most people think of the field as offering only career prospects in the IT industry. However, that’s not true. The actionable data insights that professionals extract are useful across industries.
Let’s understand the career scope of data science in different industries:
| Industry | Scope |
|---|---|
| Retail | The components of data science are useful for personalising product recommendations, understanding customer behaviour, and forecasting customer demand. |
| Finance | Data science helps to create trading algorithms, assess credit risk and automate fraud detection. |
| Healthcare | Medical organisations utilise the field to streamline hospital operations, tailor treatment plans, and predict disease outbreaks. |
| Manufacturing | The sector leverages data science to forecast inventory, ensure quality control, and enable predictive maintenance. |
| Cybersecurity | With the help of data science, professionals can identify threats and track suspicious activities in real time. |
What is the Scope of Data Science in India in 2025?
The field of data science is widely growing in India. According to International Market Analysis Research and Consulting (IMARC) Group, the scalability of data science will reach USD 2,551.2 million by 2033.
Such a prediction makes the current scope of data science in India quite promising. How is that possible?
Firstly, the field plays a crucial role in collecting and understanding data for companies. Using these data, companies can make appropriate business decisions.
Businesses and organisations leverage technology and software to capture data. To perform the practices, they will require skilled professionals who can interpret the data. Thus, the demand for professionals across sectors is also on the rise.
Though the demand for data science professionals is increasing worldwide, India has an advantage in the scale of its demand. The country’s education market is projected to grow to up to USD 2.04 billion by 2028.
Moreover, many tech leaders are keen to invest in the Indian data science landscape to build start-ups. As a result, the field’s career scope is also in high demand.
What is the Scope of Data Science Abroad?
Global technological advancement is rapidly integrating machine learning, cloud computing and AI into data science. Such integration increases the demand for data science professionals across borders.
As the demand for data science professionals is on the rise, the scope of data science abroad also seems promising. Global exposure to data science enables individuals to access cutting-edge technology. It includes infrastructure such as Azure and AWS.
Moreover, you can develop cross-cultural communication skills and an essential international network that would advance your career options after data science. From business intelligence analysts to data engineers, there is a myriad of job roles that you can opt for.
Data science is a core professional field in many countries. That includes the USA, Canada, Germany and Australia. Students who want to make their way in the international data science landscape can do so in these countries.
What are the Eligibility Criteria for a Data Science Course?
In India, data science is one of the best career options after graduation. Anyway, Indian parents have a notion that science is a rewarding career path. Hence, individuals passionate about statistics and computer science can pursue this field.
Data scientists, data engineers, and data analysts are among the top career options in data science. But before you get into the job roles, it is essential to understand the eligibility criteria for a data science course.
From undergraduate programs to postgraduate courses, data science offers students a range of opportunities.
- To enrol in an undergraduate data science program (B.Sc/B.Tech), students should complete 10+2. They should have a background in science, including mathematics and statistics. Additionally, they should have 50-60% marks in their exam.
- For the post-graduation program (M.Sc./Diploma), you should have a Bachelor’s degree in the relevant field. That includes Computer Science, Engineering, Mathematics and Statistics. Also, you must have 50-60% marks in the examination.
Must-Have Skills for Data Scientists
To become a data scientist, you need to have both technical and soft skills. Using these skills, you can make a prosperous career in data science.
The following are the technical skills that you should know:
Technical Skills
The following are the technical skills that you should know:
- Big Data: Working with large data sets with tools like Hadoop and cloud platforms like Azure, GCP and AWS.
- Programming: Be proficient in languages like R and Python for crucial data analysis and manipulation.
- Statistics and Probability: The skill will help you understand the principles of data analysis and model building.
- Data Wrangling: To clean, transform and organise raw data.
- Data Visualisation: Enables data scientists to create compelling visuals that explain complex data to different audiences.
Soft Skills
Data scientists should also develop specific soft skills to advance in the field. These skills include:
- Problem-solving: A strong aptitude for detecting problems and offering creative solutions using data.
- Communication: The ability to demonstrate technical findings to both technical and non-technical audiences.
- Intellectual curiosity: An inherent urge to learn and explore data to find new data patterns.
- Business acumen: Understanding business context to ensure the data analysis is relevant and drives value.
How to Start a Career in Data Science?
The coming years offer a promising outlook for data science careers. Seeking a career in the field will provide you with access to different industries. Also, the salaries are competitive.
To start a career in data science, you can consider the following tips:
- Gain a strong foundation in mathematics, statistics and computer science.
- Learn programming languages to understand how data processing works.
- Acquire domain-specific knowledge that you’re interested in. It can include marketing, finance and healthcare.
- Create a portfolio and showcase your skills through research papers, practical projects and open-source contributions.
- Work in real-world projects through internships and entry-level jobs to hone your technical and soft skills.
Understanding the Salary in Data Science
Wondering what the data science career salary looks like? Well, that depends on many factors. Your job role, skills, and position are significant factors in determining a data science salary package.
The following is the salary breakdown for data science professionals, depending on their proficiency levels:
Freshers
The salary for freshers who aspire to be a data scientist can expect salaries ranging between INR 5 LPA and INR 8 LPA. Aspirants should have skills in SQL, Python and ML algorithms to advance their career as a data scientist.
Experienced
Individuals applying for mid-level positions can expect salaries between INR 12 LPA and INR 18 LPA. For senior-level professionals, such as Chief Data Officers, the salary range is INR 35 LPA and above.
Overall, choosing a career in data science can offer lucrative salaries.
Future Scope and Trends in Data Science
The rapid growth of data science makes its future scope quite rewarding. The potential for continuous rise opens up an array of career opportunities for individuals. To make the best of their careers, data scientists also provide significant trends.
Let’s learn about the future scope and trends in data science:
- AI and machine learning will continue to grow. That leads to the creation of more advanced algorithms and models. Using these modes will enable professionals to make more accurate business predictions.
- The reliability of data-driven insights is rising among businesses and organisations. Due to the surge, demand for data scientists and professionals will grow significantly.
- NoSQL, Hadoop and Spark are big data technologies that are becoming very popular. The popularity of such technologies makes more room for the storage and processing of massive amounts of data.
- The future also expects growth in the Internet of Things (IoT). As a result, professionals can extract more data insights from connected devices.
- The growth of data science makes ethical considerations extremely important. That includes data privacy and bias. Keeping these issues in mind, data science professionals will build ethical frameworks for data collection, use and analysis.
Dive into the World of Data Science to Find a Successful Career
The continuous growth in technology makes data science an integral part of the process. Trends like Artificial Intelligence and Machine Learning are here to stay, which is propelling the scope of data science.
The need for data-driven insights is witnessed across different sectors. To cater to these needs, companies require professionals. As a data scientist or data engineer, you can secure a great future.
If you have a strong aptitude for understanding large data sets, choosing data science as a career option would be ideal. Through undergraduate and postgraduate programs, you can gain fundamental knowledge and skills in the field.
Are you still unsure about your career in data science? Then join the top Education Fair in India. We at Career Planner organise educational events to connect students with top industry leaders and recruiters.
Our goal is to articulate the scope in different domains to students. From traditional areas like business and marketing to emerging fields like data science and machine learning, we provide one-on-one counselling to students, helping them make better career choices.
Explore our educational seminars and find the best career options in data science.
Frequently Asked Questions
1. What are the best career options in data science for girls?
Girls can pursue various career paths in data science. The popular ones include Data Scientist, Data Engineer, Machine Learning Engineer and Data Analyst, which offer great career opportunities for women in data science.
2. Which is the best career option: data science or machine learning?
Data Science and machine learning are closely intertwined. None of them is better than the other. Students who are passionate about analysing data can choose data science as a career path. However, individuals who want to build intelligent systems capable of prediction can opt for machine learning.
3. Which is better, AI or data science?
AI is an integral part of data science. Hence, students who want to learn how to create models that can make predictions can pursue data science courses.
4. What are the career options after a B.Sc. in data science?
A BSc in Data Science can unravel a wide range of career opportunities. After the program, you can pursue careers in data science, including Data Scientist, Data Analyst, and Data Engineer.
5. Is data science a good career in India?
The impact of digital transformation and AI can help you pursue a career in data science in India. With the high demand for data-driven insights in companies, the domain can be rewarding for the country.
6. What is the scope of data science with Python in India?
Python is a core programming language for data scientists. Professionals can extract large amounts of data to perform accurate analysis using Python. The high demand for data-driven insights offers a rewarding scope of data science in India with Python.
7. Is there any scope for data science in project management?
Data science involves the collection and analysis of vast data. Based on these insights, businesses can make improved decisions. Thus, there is a significant scope of data science in project management.
8. Is a Master’s in Data Science Worth It?
Individuals who want to grow their careers in data science can opt for a Master’s degree. The program will provide knowledge and skills in core data science concepts, including data manipulation and analysis, statistics, and data visualisation. Such a program can also help you get lucrative salaries.
9. What is the scope of data science for freshers?
The scope of data science for freshers is quite promising. With data science degree programs and courses, you can find career options as an entry-level data analyst, machine learning engineer and data engineer.
10. Is there scope for research in data science?
The field of data science is continuously evolving. In such a scenario, data science offers immense scope in research.
11. Is it good to do a B.Tech in Data Science?
Data Science is relevant across industries such as healthcare, finance, and e-commerce. With a B.Tech in Data Science, passionate students can unlock a myriad of high-paying job roles.
12. What is the scope of business analytics in data science?
Business analytics has a vast scope in data science. It covers core areas such as operations optimisation, improved decision-making, and enhanced customer experience. Professionals use data to build strategies and forecast trends for businesses.
13. Do Apple and Google Hire Data Scientists?
Apple and Google are global companies that hire tech professionals. Since Data Science is an integral part of technology, both companies hire data scientists.
14. Which is better, computer science or data science?
Both computer science and data science are rewarding fields. As a result, there is a high demand for professionals in both areas. Depending on your interests, you can choose either field.
15. Is It Possible to Switch Careers to Data Science?
Yes, switching to a career in data science is simple. Students with a science background can easily switch to data science.
