Data Science VS Software Engineering - Know The Career Path

blog_auth Blog Author


published Published

Feb 15, 2023

views Views


readTime Read Time

16 mins

Tabel of the content


The data science market has been valued at USD 95.3 billion in 2021 and is estimated to reach around USD 323 billion by 2026. Thus, its compound annual growth rate (CAGR) is 27.7%. On the other hand, the software engineering market is estimated to be valued at USD 123.5 billion and had a CAGR of 11.26% during 2020-23.

Data science and software engineering are usually misunderstood domains. Data science, as the name suggests is an interdisciplinary domain that combines mathematics and analytics. A data scientist uses a huge amount of data to examine different areas of prediction, understanding, and exploration. Their major role is to analyze data and apply its results to different areas of an organization. They align their results with expertise to achieve overall results.

Being a data scientist requires special knowledge in statistics, mathematics, and analytics. It is an individual discipline, conceived by William S. Cleveland. It is a fast-growing field that was also declared the second-most promising in the United States of America in 2021.

On the other hand, software engineering involves developing software systematically, using principles of engineering. A software engineer delivers on the requirements of users, and determines, builds, and tests software applications.

Based on the definition by German computer scientist Fritz Bauer, software engineering is the establishment and use of engineering principles to develop economic software that is both reliable and efficient. Thus, it refers to system analysis and computer programming and may involve different areas including science, economics, management science, and system engineering. It serves as the foundation for understanding software and computer science – helping the estimation of resources in economics.

Usually, you can apply to be a software engineer with only a bachelor’s degree, whereas an advanced degree is needed to be a data scientist. Top companies that look to hire software engineers include DoorDash, Saks Fifth Avenue, Netflix, Amazon, Adobe, and Capital One.

Salary Difference between data science and software engineering

Salary Range of Data Scientists:

Based on the U.S. Bureau of Labor Statistics, management analysts earn an average of USD 126,830 a year. The number varies based on the years of experience, location, and job responsibilities. According to Glassdoor, the national average is around USD 121,172 whereas, according to the U.S. News and World Report, the median salary is about USD 100,190. Once you gain some experience and reach the managerial level, you can expect a yearly salary of between USD 210,000 and 275,000.

Salary Range of Software Engineers:

According to statistics from Built In, the average base salary of a software engineer is about USD120,042 whereas the median pay of a software engineer in 2021 was about USD 109,020 according to the U.S. Bureau of Labor Statistics. The national average is about USD 101,760 according to ZipRecruiter. The majority of companies are looking for software engineers, including big companies like Adobe, DoorDash, Hulu, Twitter, Sam’s Club, PayPal, IBM, Zoom, PlayStation, Massachusetts General Hospital, Boeing, Zillow, Squarespace, Johnson and Johnson, and Lincoln Financial Group.

Data Science

Certification Course

100% Placement Guarantee

View course

Difference between data science and software engineering

The major difference between a data scientist and a software engineer is the way they work. A data scientist works around data to generate valuable business insights that help solve business-related and real-world problems. However, a software engineer develops systems and software for businesses and organizations, applying engineering concepts to software development and maintenance.

Benefits of Data Science Vs Software Engineering

Both data science and software engineering require you to have programming skills and knowledge of statistics and machine learning. However, software engineering requires you to focus more on coding languages. Both these career choices are highly rewarding and in demand. Thus, the choice entirely depends on individual interests. You can learn about both of these courses on software development. Get started with your journey by enrolling in our best program today.

Qualifications of Data Scientist Vs Software Engineer

Skills of a data scientist

Data scientists are required to have strong analytical skills. They should be able to create data models to construct analytical models. Knowing only one programming language might not be very helpful. Hence, data scientists need to be more familiar with Python, R, Java, or SQL. Moreover, once the raw data is processed and analyzed, one needs to recognize the trends, disparities, and oddities in it. Accordingly, you need to have the following skills.

  • Familiarity with a toolkit, cloud tool, and command line
  • Mathematics and statistics
  • Data wrangling and pre-processing skills
  • Data visualization
  • Communication skills
  • Quick learner and ethical skills

A master’s degree is usually desirable for a majority of data scientist positions that pay a good salary. Typically, data scientists start with a bachelor’s degree in computer science, data science, or a related field. In general, the career opportunities and salary expectations of these candidates vary based on their education levels.

Skills of a software engineer

A software engineer typically needs a bachelor’s degree in a related field, such as computer science or engineering. Strong programming skills are also required to qualify for this job. Ensure that you do several internships beforehand to get better opportunities later on. To be a successful software engineer, you must acquire and retain the following skills:

  • Math, science, and design techniques
  • Strong analytic and problem-solving skills
  • Multi-tasking, team player, and attention to detail
  • Experience in various programming languages
  • Fluency in one or more computer coding languages
  • Strong communication and interpersonal skills

Career paths of a Data Scientist Vs Software Engineer

Data scientists are required to make various decisions at different levels of the organization. They should be able to work on different data-related projects and work around them accordingly. They also need to have a strong grasp of the organization they are working for and be specific in the data collection process. With experience, you will be able to predict consumer behavior and improve your working standards to take the next steps in your career.

Your career as a data scientist may require the same skills as that of a software engineer, namely, coding and analytical thinking. However, data scientists also require more specialized knowledge of advanced math and data manipulation.

Software engineers, on the other hand, have one of the most sought-after careers in the technology industry. According to the Bureau of Labour Statistics, there will be an increase of around 22% in the jobs in this sector by 2030. Various industries hire software engineers and you will enjoy good job security. Software engineers are expected to be more innovative and crafty.

As businesses continue to improve and come up with new technologies, the demand for software engineers will also keep increasing. Therefore, this industry will offer a lot of upward growth and your opportunities will increase exponentially as you garner more and more experience.

Data Science

Certification Course

Pay After Placement Program

View course

Steps to becoming a data scientist

1. Get a Bachelor's degree:

    • Start with a bachelor’s degree which requires at least four years to complete. During this time, you should choose your majors wisely. You may choose among data science, computer science, or mathematics.
    • Opt for internships and collect relevant skills and experience.
    • Go for professional certification courses and improve your skills on the way.
    • Get entry-level experience by applying to jobs around you. You may look for entry-level data engineers, market research analysts, and data analyst posts.

2. Attend a data science boot camp:

    • Earn a bachelor’s degree in any related field.
    • Complete a data science boot camp, which provides intensive career training in less time than most college or degree programs.  
    • Do an internship.
    • Go for a professional certification course to level up.

3. Get a master’s degree

    • Earn a bachelor’s degree in any related or unrelated field.
    • Earn a master’s degree in data science, which usually takes up to 1-2
    • years to finish.

Steps to becoming a software engineer

1. Select a language to learn

Software engineers mostly focus on coding. Hence, you need to be proficient in at least a couple of programming languages like Python, Javascript, C++, Ruby or Java.

2. Earn a degree in a related field

The next important thing you need to take care of is earning a degree in computer science. Start with a bachelor's degree and major in computer science.

3. Add more supplements to your studies

Along with getting a degree, you need to read relevant books and gain supplementary knowledge on the subject matter. This will help you gain a deeper insight into your coding languages. Accordingly, you can enrol in advanced courses like those offered by StarAgile. They provide a reliable set of courses with many important tips for developers looking to develop their technological expertise, problem-solving skills, and language proficiency.

4. Be in touch with experienced developers and learn from them.

You should also start reading codes written by experienced developers. Learn to find a practical implementation of your coding languages in the industry. Having mentorship and real-life experiences will aid your career path.

5. Find a community of software engineers

Once you're through with your supplementary studies, you need to find a community of software engineers to be surrounded by like-minded people. Accordingly, you can network and further develop your skills to get an edge over the competition.

6. Build projects and master your interview skills

Along with real-life experiences, you need to build projects and master your pre-interview and other tech-related skills. While seeking employment, you may be asked a couple of questions in your interview that test your knowledge of your coding languages. As you learn to code and build projects, you should slowly build your professional network.


Jobs of Data Scientist Vs Software Engineer

Jobs of a Data Scientist

  1. Data Analyst
  2. Data Architect
  3. Statistician
  4. Database Administrator
  5. Business Analyst
  6. Data and Analytics Manager

Also read business analyst vs data analyst

Jobs of a Software Engineer

  1. Principal software engineer
  2. Software Developer
  3. Software integration engineer
  4. Mobile Developer
  5. IT Consultant
  6. Computer Systems Analyst

Overall, whichever career path you choose, you can enter the market by gaining more data science training or software engineering skills. Getting the right experience is just as if not more important than having a degree. Ensure that you constantly keep updating your knowledge and keeping up with industry trends. To add more to your skills before joining the industry, you can apply for courses from StarAgile.

Share the blog

Keep reading about

Card image cap
Data Science
What Does a Data Scientist Do?
calender04 Jan 2022calender15 mins
Card image cap
Data Science
A Brief Introduction on Data Structure an...
calender06 Jan 2022calender18 mins
Card image cap
Data Science
Data Visualization in R
calender09 Jan 2022calender14 mins

We have
successfully served:


professionals trained




sucess rate


>4.5 ratings in Google

Drop a Query

Email Id
Contact Number
Enquiry for*
Enter Your Query*