The differences between a software engineer and a data scientist

Data science and software engineering are popular, high-paying jobs offering enormous career potential and the opportunity to work in a wide range of industries — but which is perfect for you? In this guide, we lay down all the similarities and differences between the two.

What does a data scientist do?

Data scientists collect vast amounts of data from various sources. This serves as the foundation step for the application of further methods of analysis among which may include the creation of probabilistic models to identify trends in the data. Ultimately, they create machine learning pipelines to help businesses understand their customers better and personalise their offerings to customer preferences. In other words, data science in technology concerns data products, infrastructure and machine learning for decision-making.

A Data scientist needs to excel in maths and statistics. They must be curious, creative and able to think critically. They must ask themselves and more importantly be able to answer questions such as: What am I able to do with this information? What patterns lay yet undiscovered? To comprehend the potential of the data, they need to display a flair for problem-solving, as well as a passion for answering questions that have yet to be asked. Data scientists have a high level of education. According to an industry survey, 88% of data scientists have a master’s degree or higher, and 46% have a Ph.D.

You’ll also need some knowledge of computer programming to create the models and algorithms required to mine data in massive warehouse computing facilities. That’s where an online master’s computer science program can help. Baylor University’s program focuses on ethical considerations, innovative thinking, technical skills, and global trends impacting science and technology.

What does a software engineer do?

A successful software engineer understands how to use the appropriate architectures, platforms, and programming languages, to create everything from video games to a networked system. In addition to developing their own systems, software engineers test, maintain, and upgrade software developed by others. Software engineers are often classified as either systems developers or application developers. As a systems developer, you will create computer systems and networks that front-end applications will require. Working as an application developer is more customer oriented. For example, you could work on the system’s front or back end, building software the end user would interface with.

To ensure that software products are of high quality, reliable, and user-friendly, software engineers often work in teams and collaborate with other experts such as designers, project managers, and quality assurance testers. In addition, they may also work on software systems such as desktop applications, mobile applications, operating systems, and web applications. Therefore, the online master’s in computer science mentioned above could also benefit aspiring software engineers as the skills required for each role can easily be suited to the next.

Skills required

There is some overlap between data science and software engineering abilities. The most critical skills for becoming a data scientist are programming, machine learning, statistics, and data visualisation. Of course, various specializations may require more skills. Still, it’s reasonable to conclude that these are the base necessities for pursuing a career in data science. If you want to work in software engineering, you’ll need a few more intangible abilities. You must be able to program and code in several programming languages. You must also be able to adapt to diverse situations, find creative solutions to problems, work well in teams, and be open to learning.

Every time I write one of these essays contrasting jobs, I’m amazed by how similar they can be. These positions use a lot of the same languages and technologies. For example, as a Data Scientist, you may find yourself programming or coding so much that you feel like a Software Engineer on some days, whereas as a Software Engineer, you may work on model deployment and feel like a Data Scientist on others. However, there are some subtle differences that we will go over next.

Differences between the two

There are numerous distinctions between data scientists and software engineers, such as:

Coding responsibilities 

Although data scientists and software engineers are responsible for coding and programming, their roles in a system differ. Data scientists generally focus on the data part of a system, which includes indicators like sales, customers’ reactions, or interactions from websites. They understand how to examine the data and apply it to better the company’s offerings. They may engage with and alter programs, and websites as data experts while reviewing and using data with other management. Software engineers typically concentrate on the actual design of the websites, firewalls, and software they create, test, or develop for the firm.

Working environment 

While these roles can be found in similar work contexts and even on the same team, they can also be found in entirely different environments and sectors. Software engineers typically work in IT, developing and maintaining software programs and systems. Bigger firms with their own IT departments and companies that generate software for others may employ them. Data scientists may work in these locations and any organisation that handles a large amount of data. This means that a data scientist may operate in a larger number of industries, such as health care, retail, technology, and finance.


The writing and maintenance of software stacks has become so complex that school is frequently the last time a software developer builds something independently. Software engineers often operate in thousand-person teams. Many data science projects are new and small enough to be managed by a small group or even a solo data scientist. That is not to say that scientists work in isolation. Still, their roles will come into contact with far fewer people than software engineers.


Lastly, there is one more question. Data Scientist vs. Software Engineer – Which occupation is better? Data Science and Software Engineering both require programming expertise. While Data Science encompasses statistics and Machine Learning, Software Engineering is more concerned with the design, maintenance and testing of software. These professions are in high demand and highly rewarding. Finally, it is determined by your area of interest. Although the relevance of data science is growing, it will never surpass that of software engineering because we will need them to construct the software on which data scientists work.