StarAgile
Oct 04, 2024
3,100
16 mins
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.
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.
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.
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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.
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.
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.
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:
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.
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1. Get a Bachelor's degree:
2. Attend a data science boot camp:
3. Get a master’s degree
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.
Also Read: Data Science vs Machine Learning
Also read business analyst vs data 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.
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