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 career 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. This article will help you gain an understanding of the difference between software engineering and data science.
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 third best in America in 2020.
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 21% through 2028. 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.
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:
- Time management
- Attention to detail
How Much Can You Earn as a Data Scientist or Software Engineer?
According to indeed.com, the average base salary of a data scientist in the United States is $122,839 a year. Depending on their experience, skills, and location, an entry-level data scientist can earn anywhere from around $103,884 a year. Someone with three to four years of experience can earn as much as $141,550 a year.
The salary for a software engineer, on the other hand, averages at around is $109,330 per year in the United States. A graduate can earn somewhere around $102,160 a year, whereas a senior engineer with more than six years of experience can earn around $120,052 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 data science appeals to you, Thinkful’s Data Science Immersion course offers an accelerated online program of classes, mentorship, and professional guidance designed to get you a career in data science, fast. If you need to keep working while you learn, try our part-time Data Science Bootcamp.
If you’re more interested in software engineering, Thinkful’s Software Engineering course is a fast-tracked, full-time program of online classes, mentorship, and career coaching to help you become a highly paid full-stack web developer. 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.