The Indian IT industry is one of the most significant contributors to the global economy, generating billions of dollars annually. And when in 2022, the world faced a downturn and tough economic times caused by various factors, the Indian IT industry could not only survive but thrive. The IT industry accounted for 7.4% of India's GDP in FY22, and it is expected to contribute 10% to India's GDP by 2025.
That's why it's safe to say that there will always be a great demand for IT professionals in India. But what career path to choose? We bet you've already heard many times that data science and software development are the skills of the future. Despite the economic situation, the number of investments in data science and software development has remained the same.
Moreover, these two job profiles have some common skill sets, so deciding whether to put your feet on the door as a data scientist or software developer becomes tricky. Let's discuss both these positions in detail.
Who Are Data Scientists and Software Developers? Their Roles and Responsibilities
Data scientists have become very demandable within the last few years as big data technologies integrate into more and more organizations. Data scientists are professionals who use scientific methods to collect, analyze and interpret output from data. They are also responsible for creating actionable plans depending on the data results. Therefore, they need to create algorithms and data models to forecast outcomes. Data scientists should also collaborate closely with business leaders to help with company objectives and identify data-driven strategies for achieving those goals.
Common Duties and Responsibilities of Data Scientists include:
Identifying relevant data sources for business needs and extracting usable data from them.
Deploying data tools such as Python, R, SAS, or SQL.
Using ML tools to select the required features; create and optimize classifiers.
Collecting structured and unstructured data and carrying out its preprocessing.
Sourcing missing data.
Enhancing data collection processes.
Organizing data into usable formats.
Creating predictive models.
Developing ML algorithms.
Enhancing the data collection process.
Processing, cleansing, and validating data.
Analyzing data to find patterns and solutions.
Setting up data infrastructure.
Developing, implementing, and maintaining databases.
Assessing the quality of data.
Generating information and insights from data sets and identifying trends and patterns.
Creating visualizations of data.
Preparing clear reports for executive and project teams.
A software developer is a professional responsible for designing, programming, building, deploying, and maintaining software using many different skills and tools. They can create software for government, healthcare, education, defense, manufacturing, businesses, and consumers. They may work closely with clients to determine their needs to ensure the quality of a final product. Depending on the setting, a developer may work alone or in a team with other programmers.
Common Duties and Responsibilities of Software Developers include:
Producing clean and efficient code based on the needs of the client.
Verifying, testing, and deploying software programs and systems.
Fixing and enhancing existing software.
Working with other developers to design algorithms and flowcharts.
Integrating software components and third-party programs.
Troubleshooting, debugging and upgrading the software.
Recommending and executing improvements.
Creating technical documentation.
Communicating with clients and understanding their needs.
The Skills for Data Scientists and Software Developers
These specialists need two types of essential skills – technical and non-technical (also called hard and soft skills).
Some of the most important technical data scientist skills are:
Good knowledge of statistical analysis and computing.
Proficiency in Machine Learning.
Knowledge of Deep Learning, Probability, and Statistics.
Processing of large data volumes.
Data Visualization.
Data Wrangling.
Mathematics.
Solid knowledge of programming.
Statistics.
Big Data.
Artificial intelligence basics will be a bonus.
Solid programming knowledge means familiarity with various programming languages like Python, Perl, C/C++, SQL, and Java. And speaking about analytical tools, here, the most popular ones are SAS, Spark, Hadoop, Hive, Pig, and R.
Some of the most important technical software developer skills include:
Strong knowledge of at least one programming language and framework.
Mathematics and data analysis.
Problem-solving.
Data structure and algorithms.
Source control.
DevOps.
Ability to work with different databases.
Git.
Integrated development environment.
Agile and scrum development methods.
Software development lifecycle.
Proficiency in tools for debugging and software testing.
As mentioned before, both software developers and data scientists should have a healthy balance of hard and soft skills. That’s why such non-technical skills are quite important:
Open-mindedness and adaptability.
Critical thinking.
Good analytical and strategic skills.
Patience.
Creativity.
Confidence.
Intrinsic motivation.
Teamwork and collaboration.
Besides that, these specialists should possess the strong business acumen to discern the problems and potential challenges. Also, they need to have good communication skills to clearly explain their findings to clients or team members who don’t have the same professional background.
Salary Comparison: Data Scientists vs. Software Developers
Data Scientists are very well-paid in India. Actually, they are the most popular profession in the Indian IT market, with wages generally 36% higher than the other professions.
As per the data collected from Ambitionbox.com, Data Scientists in India earn between ₹ 3.8 Lakhs to ₹ 26.0 Lakhs with an average annual salary of ₹ 10.0 Lakhs. Their salary largely depends on their experience - with an increase in every year of experience, a data science professional’s salary increases exponentially.
Software Developer salary in India is also pretty high compared to the vast majority of other professions. It ranges between ₹ 1.8 Lakhs to ₹ 13.0 Lakhs with an average annual salary of ₹ 4.8 Lakhs.
The average salary of Software developers is highly regarded, and just like with the data scientists post, it raises with your experience.
Please, note that according to Indeed, the highest paying Indian cities for both these jobs are Hyderabad, Chennai, Bengaluru, Mumbai, Pune, Gurgaon, Noida, and New Delhi.
The Number of Job Openings
When it comes to job openings, it becomes obvious that the competition for data scientists is much tougher. India’s number 1 job search website, Naukri, now lists about 800 job openings for data scientists and more than 92,000 job openings for software developers.
What is notable, out of all the software developer openings, 82,141 of them list Java among the top required skills.
Career Paths for Data Scientists and Software Developers
Now, let’s now talk about how you can progress if you choose a career in Data Science and Software Development.
If you’re going to choose Data Science, then, most likely, your career path will look something like that:
Data Scientist → Middle Data Scientist → Senior Data Scientist → Machine Learning Engineer → Lead Data Scientist → Chief Data Officer
And in case you’re going to become a software developer, then a successful career path shall be as follows:
Junior Software Developer → Middle Software Developer → Senior Software Developer → Tech Lead → Team Manager → Technical Architect → Chief Technology Officer
The Benefits of Both Roles
Well, is data science a good career? Of course, yes, data science is currently a very attractive career path for many professionals. Since businesses rely more and more on data to drive their processes and growth, the demand for good data scientists will continue to grow. With that, digital science is still in the promising stage, so you have an opportunity to jump on this bandwagon and experience significant growth opportunities in the future. Yet, data science may be a tricky career for newbies since it requires learning too many technologies. That’s why it may be a smart choice for “future” data scientists to start with software development and eventually acquire additional skills needed for data processing.
What about software development? This is already a well-established sphere that not only offers various career options (independent contractor, freelancer, or in-team player; front-end, back-end, full-stack or mobile app developer). It also boasts higher learning prospects because nowadays, there are lots of learning communities and online tools that can help you learn different programming languages.
The Future?
The biggest concern of data scientists is that their work in the future can be largely “automated” and partially replaced by artificial intelligence. Still, we believe that in most cases data scientists will still be needed to oversee the results of all these automated processes. Hence, more focus on coding and AI skills.
Also, data scientists are predicted to face a growing demand in the field of cybersecurity since the world has become increasingly reliant on digital information, where cybersecurity has become extremely important.
In addition to that, we expect that data scientists will face an increasing prevalence of cloud computing, so eventually, they will need to master cloud-based data processing tools and techniques. At the same time, data scientists need to become even more business-minded.
Regarding software engineering, the future surely looks bright, keeping in mind the increasing tech demands of the world. In 2023, the demand for software developers has already risen by nearly 17% across all industries, according to the Opportunity Desk.
The thing is, every industry needs software solutions to streamline work and make all the processes more effective and accurate. And with emerging technologies like AL, cloud services, blockchain, cybersecurity, and other advancements, companies are looking for high-end software solutions. Thus, it’s safe to say that the demand for skilled developers is not going down anytime soon. Instead, the rise is likely to face a boom.
However, you should bear in mind that new technologies demand new skills, so software engineers need to stay updated with the trends as well. Along with upgrading skills, developers will also need to possess high ethics and integrity to work in data privacy and AI applications.
With all of this said, the best way to predict the future is to create it.
Conclusion
Today, we discussed the top in-demand jobs in 2023 in India's growing tech industry. Both these job profiles offer great opportunities for growth and learning, and both require a great deal of technical knowledge and expertise. But while Data Science focuses on statistics and Machine Learning, Software Engineering targets coding. Ultimately, the decision comes down to individual interests, skill sets, and strengths.
And if you gravitate toward software development, CodeGym can help you with mastering this profession with minimum hassle and with maximum engagement. You’re welcome to join our course “Java Developer Profession”!
Moreover, these two job profiles have some common skill sets, so deciding whether to put your feet on the door as a data scientist or software developer becomes tricky. Let's discuss both these positions in detail.
As per the data collected from Ambitionbox.com, Data Scientists in India earn between ₹ 3.8 Lakhs to ₹ 26.0 Lakhs with an average annual salary of ₹ 10.0 Lakhs. Their salary largely depends on their experience - with an increase in every year of experience, a data science professional’s salary increases exponentially.
Software Developer salary in India is also pretty high compared to the vast majority of other professions. It ranges between ₹ 1.8 Lakhs to ₹ 13.0 Lakhs with an average annual salary of ₹ 4.8 Lakhs.
The average salary of Software developers is highly regarded, and just like with the data scientists post, it raises with your experience.
What is notable, out of all the software developer openings, 82,141 of them list Java among the top required skills.
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