Software Engineer vs Data ScientistMay 9, 2022
The role of a Data Scientist as well as a Software Engineer is currently in high demand among all the tech jobs. A software engineer is a well-established career that many computer science graduates prefer to pursue. Whereas, data science is a fairly new career that many people are not aware of, but offers a really high salary. There are many students and professionals who are in a dilemma when it comes to choosing between these 2, therefore, we bring to you a comprehensive comparison between Software Engineering and Data Science.
In this article, we will be comparing both of these career options, which have their own similarities and differences. We will also discuss how there is a better Data Science Course in India with placements after completing an online certification. The focus of both the job roles is to solve business problems, and they both deal with some kind of data, automation, and testing.
These two careers go hand in hand and therefore in most cases, a software engineer can also decide to become a data scientist and vice versa. Here in this article, we will be highlighting the characteristics of both the positions, so that by the end of the article, you can decide which career works best for you.
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Software Engineer vs Data Scientist: Who are They?
Software engineers and data scientists are both tech jobs, but their responsibilities make them different from each other.
- Software Engineers are computer science professionals who use their knowledge and skills to build software, solve software issues, and provide infrastructure, maintenance, and testing.
- They have knowledge of programming languages, software development, and operating systems, and also have good analytical skills.
- Data scientists are data analytics experts who have the skills to solve complex problems.
- They usually deal with structures and unstructured big data to find patterns, trends, and conclusions.
- They are more focused on defining a problem statement, querying data, performing exploratory data analysis, developing models, and interpreting results.
- Their usual work includes collecting a huge amount of data and converting it into a usable format.
Software Engineer vs Data Scientist: Importance
Both software engineers and data scientists are required for the growth of an organization. The importance they have in an organization are:
- Software engineers are required in almost every industry, as every business needs some type of specific software.
- Also, if something breaks within the application portfolio or an organization, then these software engineers are required for a quick, efficient, and effective fix.
- They are important because they build new software products for the organizations. They understand the requirements of the user and build something that wasn’t there before.
- Data is being produced in a tremendous amount from various sources today, and it holds the key for the companies to understand their clients.
- Data scientists are those professionals who help the organization understand the needs of the customer by analyzing a huge set of data.
- They help businesses to tailor products best suited to the requirements of their potential customers.
- Overall, they help businesses make better decisions that lead to the growth of an organization in terms of customer interaction, sales, profits, etc.
Software Engineer vs Data Scientist: Career and Salary
Software engineering and data science are among the most demanded tech jobs in the current market, but they differ based on the demand-supply ratio and the salary offered.
- Software development is a high priority for a majority of IT companies and thus software engineering is a career in demand.
- According to global software development statistics, about 57% of IT companies plan to devote more attention to software development.
- There were around 23.9 million software engineers in 2019, and the number is estimated to grow up to 28.4 million by 2024 [Source: Seed Scientific].
- The average salary of software engineers in India is expected to be around ₹5,95,943 per annum [Source: Payscale].
- With the rapid digitalization of business and services, India has become the second-largest hub for data science in the world.
- Since 2019, the hiring in the data science industry has increased by 46%.
- It has been predicted that by 2026, India will have more than 11 million job openings in data science.
- Also at the end of August 2020, around 93,000 jobs in data science were vacant. This shows that there is demand for data scientists but the supply is short [Source: India Today].
- The average salary of a data scientist in India is expected to be around ₹8,64,359 per annum [Source: Payscale].
Software Engineer vs Data Scientist: Qualifications and Skills
The qualifications and skills that one needs to build a career as a software engineer and a data scientist are explained below.
- One needs to have a bachelors’ degree in a relevant field like computer science engineering to start a career as a software engineer.
- They should also have knowledge of at least one object-oriented programming language.
- A degree does not really matter to build a career as a data scientist if one has the required skills. But most data scientists usually have a postgraduate degree.
- For an easy start, one should have a background in computer science, engineering, social science, data science, mathematics, or statistics.
- They should have in-depth knowledge in any of the programming languages like Python, R, and SQL.
- They should have technical knowledge of Python coding, Hadoop platform, Apache Spark, Machine learning, and Artificial intelligence.
Looking at the differences above, it might still be a tough choice to make. The question ‘Which profession is better?’ still stays in the mind, as both the careers are in demand and highly rewarding. The answer totally depends on the interest of an individual. One should think of what are they expecting out of their career, what are they interested in, what skills they possess, and what skills they are willing to learn.
Keeping your preferences at the center of decision making will land you up at a better place.