Data Science vs Software Engineering

Terms like big data and data science are slowly becoming a part of our everyday vocabulary. While software engineering is already a well-established discipline, many people interested in pursuing a career in computer science or a related field might not be aware of data science. This is partly because data science is a fairly new career option.

If you’re willing to explore a tech job but you’re undecided between a more traditional choice like software engineering, or the newer field of data science, you’ve come to the right place. Here are the key differences between software engineering and data science career paths.

What Is Data Science?

Data science is an interdisciplinary domain derived from computer science that uses several scientific processes and methods to study different kinds of data—structured, semi-structured, and unstructured. It involves using numerous technologies like data transformation, data purging, and data mining to study and analyze that data. While both data science and software engineering rely heavily on programming knowledge, data scientists focus more on manipulating large datasets.

A data scientist exploits a huge amount of data for prediction, understanding, intervention, and exploration. They focus on the value of approximation, the results of data analysis, and the understanding of its results. Like software engineers, data scientists aim to optimize algorithms and manage the trade-off between speed and accuracy. They coordinate with experts and work together to achieve a balance between the assumptions and results.

Data science requires specialized knowledge in analytics, statistics, and mathematics. Data science, as a separate and independent discipline, was conceived by William S. Cleveland, after which it became more popular across the world. Data science is a fast-growing field—the job of data scientist has been declared the second best in America in 2021.

What Is Software Engineering?

Software engineering, on the other hand, is the process of developing software by systematically applying the principles of engineering. A software engineer analyzes user requirements, then designs, builds, and tests software applications if they fulfill the set requirements.

Prominent German computer scientist Fritz Bauer defined software engineering as “the establishment and use of sound engineering principles in order to obtain economically software that is reliable and works efficiently on real machines”.

Often the term will be used informally to refer to a range of activities related to system analysis or computer programming. It’s related to several other disciplines like computer science, economics, management science, and system engineering.

Software engineering serves as a foundation for understanding software in computer science and helps in the estimation of resources in economics. It employs  management science for labor-intensive work.  It’s currently one of the  most widely chosen careers worldwide.

A Career in Data Science

Data scientists help business stakeholders meet the goals of the business through data manipulation. They usually examine methods of using data to achieve these goals, thereby maximizing the scope of business. Data scientists have to work closely with different teams such as design, sales, and marketing in order to understand the broader aims of the company. They need to have a flexible approach and be adaptable to new ideas so they can come up with fresh solutions.

As a data scientist, you need to be aware of the various decisions made at different levels of the organization. This will help you to understand how to formulate functions on various data projects and work accordingly. You’ll need to have a strong grasp of the company’s pattern of work so that you can be specific in your data collection, which will enhance your efficiency. With time and experience, you’ll learn to predict consumer behavior, which will allow you to improve your work standards.

A career in data science relies on some of the same skills as software engineering: namely coding, analytical thinking, and great communication. But data science careers sometimes require more specialized knowledge than software engineering, such as advanced math and data manipulation techniques.

Qualifications and Skills Required for a Data Scientist

Like software engineers, data scientists are highly qualified professionals. While almost half of them have a postdoctoral degree, more than 80% have at least a master’s degree in relevant fields.

To build a foundation in this field, you can start with a bachelor’s degree in computer science, social science, engineering, or statistics. While a degree builds a solid platform for your tech career, you don't actually need one to get started. Alternative education programs may suit some aspiring data professionals.

Other skills you should acquire include:

• Familiarity with a toolkit, preferably a combination of coding, SQL, cloud tool, and command line. You can pick up these skills by taking a data science course or even a software engineering bootcamp.
• In-depth knowledge of R programming
• Technical knowledge of Python coding, Hadoop platform, Apache Spark, machine learning and AI
• Good communication skills and business acumen
• Strong team skills

A Career in Software Engineering

A software engineer applies knowledge of engineering and programming languages to develop apps for computers. They’re involved in designing, developing, maintaining, testing, and evaluating software.

Computer software engineering is one of the most sought-after careers in the tech industry.  The Bureau of Labor Statistics (BLS) projected an increase in job  growth by 22% through 2030. These engineers find employment across various industries.  

Job security isn’t the only perk of becoming a software engineer. As employers compete for top engineers, they offer benefits to attract the best talent. You can expect flexible working conditions that allow you to work from home. Some employers also provide complimentary lunches, health insurance, and employee discounts.

Software  engineering is an innovative field and often leads to new discoveries.  As businesses continue to embrace new technologies and tools, the demand  continues to rise for professionals with cutting-edge knowledge and the  skills to solve complex problems.

Qualifications and Skills Required for a Software Engineer

To pursue a career in software engineering, many students opt for a bachelor’s degree in a relevant field. Most software engineers major in computer science, programming, or math.

But just like data science, a degree isn’t compulsory to get started as a programmer. In recent years, employers have been favoring practical skills over formal education programs. They understand that degrees can provide an excellent foundation but sometimes lack specific career-ready skills. Candidates with real-life experience and a proven programming track record will have more success landing a job.

It goes without saying that you’ll  need to learn how to write code to become a software engineer. Popular  programming languages include C++, C, Java, JavaScript, and Python. Each  language has advantages and disadvantages, depending on the project you’re working on.  

C++ is extremely fast and efficient, making it perfect for embedded software or apps that run on low memory devices. Java is easier to learn but has relatively poor performance for software that requires a fast execution speed.

You  should try to learn at least one object-oriented programming language.  By understanding concepts like encapsulation, abstraction, inheritance  and polymorphism, you’ll be able to quickly master many common languages used in industry.

Soft skills that will also take you far:

• Communication
• Adaptability
• Time management
• Attention to detail

How Much Can You Earn as a Data Scientist or Software Engineer?

The average base salary of a data scientist in the United States is $116,654 a year. Depending on their experience, skills, and location, an entry-level data scientist can earn anywhere from around $93,167 a year. A senior data scientist can earn as much as $142,144 a year.

The average salary for a software engineer, on the other hand, is $108,201 per year in the United States. An entry-level software engineer can earn somewhere around $76,899 a year, whereas a senior engineer can earn around $131,219 a year.

Both data scientists and software engineers enjoy high pay, great benefits, and jobs that both challenge and reward them.

Start Learning Data Science or Software Engineering

Data science is related to gathering and processing data, whereas software engineering focuses on the development of applications and features for users. A career in either data science or software engineering requires you to have programming skills. While data science includes statistics and machine learning, software engineering focuses more on coding languages.

If finding solutions through analysis and computer programming appeals to you, our Data Science course will help you become a full-fledged data scientist.

If you’re more interested in software engineering, our full-time Software Engineering course is the fastest and most proven path to a long-term career in web development. A part-time Software Engineering option is also available if you need a more flexible schedule.

Both career choices are in demand and highly rewarding. Ultimately, it depends on your area of interest. It’s a big decision, so make sure you’re informed: read up about both software engineering and data science, as well as a range of other tech careers.