Data Science vs. Software Engineering: A Fine Differentiation

Data science and software engineering are IT-based domains and play widespread organizational functions. Both domains require a wide range of programming skills from different domains. The career opportunities in these fields are increasing day by day.

The report, titled "Analytics & Data Science Jobs in India 2022," showcases the following results: Compared to the 9.4% global open jobs in June 2021, 11.6% of the total open positions came from India alone. An increase in open positions observed by captive centers, ongoing domestic company investments in establishing analytics and data science capabilities, a significant shift of domestic and foreign IT and KPO organizations to India, increased funding for AI and analytics-based start-ups in India, and an increase in open positions are all factors contributing to this growth.

With 51,149 available positions or 28.5% of the market, Bengaluru overtook Delhi NCR as the top location for analytics and data science experts for the sixth consecutive year. Employees are returning to their jobs at a higher rate than in other cities, which supports the rise.

Likewise, the demand for software engineering jobs is rising. Moreover, with the IoT and blockchain tech boom, software engineering is expected to retain its crown as one of the most sought-after degrees in India.

Data Science 

Data science compromises the collection and analysis of data for logical and valuable outputs. It deals with an extensive range of data analytics using various tools and techniques such as AI, data mining, and machine learning. It includes studying various structured and unstructured data to derive expressive information and find unseen patterns to make effective business decisions. Data science is among one of the fastest-growing domains. It is an essential aspect of any organization as it makes decisions on a factual basis. 

Software Engineering

Software engineering is a systematic method of creating software by engineering principles and comprises planning, building, designing, and testing software applications.

It is a detailed study of development, design, and software maintenance, and it manipulates the best methods and techniques for creating high-quality software. 

It is a very prevalent career option for many candidates, providing thousands of opportunities in various national and multinational organizations. 

Qualifications for Data Science and Software Engineering

Check out the qualifications needed to pursue data science and software engineering degrees individually.

Data Science

If a candidate wants to pursue their career as a data scientist, they should have completed their undergraduate and post-graduate from a well-recognized university. The degrees include:

• B. Tech or M. Tech majoring in computer science 

• B.Sc or M.Sc in statistics/mathematics 

• MBA 

Software Engineering

If a candidate wants to pursue their career as a software engineer, they should know a few programming languages such as; Java, Javascript, Python, C, Ruby, and C#. 

They should have an undergraduate and postgraduate degree from a well-recognized university. The suitable domains include the following:

• Computer Programs

• Deep and Practical Programming 

• Data Structures and Algorithms

Data Scientist vs. Software Engineer

There are a lot of differences between data science and software engineering. Here is a list of some of the main differences:

Data Science vs. Software Engineering Based on Career Opportunities

If anyone is confused about whether to become a data scientist or a software engineer, here is a well-researched section about the career opportunities in data science and software engineering. One can consider this and choose a suitable domain for their career. 

A Career in Data Science

The demand for data scientists is increasing promptly. Different opportunities are available according to the convenience of the candidates.

One can become an analyst at an entry-level or pursue specialized courses to become a chief data officer.

One can become an analyst in several domains: quantitative analyst, business analyst, marketing analyst, operations analyst, business intelligence analyst, data analyst, and systems analyst.

If anyone wants to have senior roles, they can pursue some specialized courses in data science to become a senior data scientist, lead data scientist, or machine learning engineer.

A Career in Software Engineering

The field of software engineering is very broad, so it is beneficial to make a career in this field. After pursuing software engineering, one can become a full-stack engineer, mobile app developer, software development engineer, game engineer, front-end engineer, DevOps engineer, security engineer, data engineer, back-end engineer, embedded systems engineer, and graphics engineer.

Suppose anyone wants to have a lead role. In that case, they can pursue a specialized course and become a technical architect, tech lead, chief technology officer, senior software engineer, team manager, or junior software engineer.

Data science and software engineering are IT-based domains; they play widespread functions within an organization, requiring a wide range of programming skills from different domains. The career opportunities in these fields are increasing day by day. If anyone wants to pursue software engineering in data science, now is the right time to develop their careers.

Data Science vs. Software Engineering Based on Salary Structure

Data scientists and software engineers get a good amount annually, and these domains have benefits. Salary is usually based on performance, competence, and skills. There are some variations in the pay scale of both domains.

Given below are some of the salary differences between data science and software engineering: 

Data Scientist Salary

The salary of data scientists depends on their prior experience in a particular field; in addition, an increment in their pay rate occurs every year. Salaries are different for different designations; for an entry-level data scientist in India, the annual salary is around INR 4,50,000. For a mid-level data scientist, the yearly wage is approximately INR 10,00,000, and for an experienced data scientist, the pay rate is about INR 20,00,000.

Software Engineer Salary

The salary of software engineers in India is on the higher side, and they receive a decent amount yearly. The demand for software engineering is increasing daily, so their pay rate is also enhancing accordingly. There are different levels in software engineering, and each level's salary is different. An entry-level software engineer receives around INR 3,50,000, and a mid-level software engineer receives about INR 5,60,000. The annual pay scale for an experienced software engineer is about INR 14,00,000.

Conclusion

This article was about data science and software engineering qualifications required career paths and salary. We hope you find the information helpful in choosing a career.