Data scientists and software engineers are popular, high-paying positions that offer tremendous career growth and the ability to work within a variety of industries — but which career is right for you? In this guide, we break down all the similarities and differences between the two, including salary, education requirements, top companies hiring for these roles — and much more.
What Does a Data Scientist Do?
A data scientist possesses a combination of coding, math, statistical, analytical, and machine learning skills. Their work involves using data expertise to create impact for the organizations they work for.
Here’s a more comprehensive definition from edureka!:
“Data scientists are those who crack complex data problems with their strong expertise in certain scientific disciplines. They work with several elements related to mathematics, statistics, computer science, etc (though they may not be an expert in all these fields). They make a lot of use of the latest technologies in finding solutions and reaching conclusions that are crucial for an organization’s growth and development. Data Scientists present the data in a much more useful form as compared to the raw data available to them from structured as well as unstructured forms.”
There are two main camps of data scientists, according to Sequoia: product analysts and algorithm developers. In general, data scientists focus on data insight and the development of data products.
The role of data scientist is also a popular one, ranking #3 on U.S. News & World Report’s list of Best Technology Jobs.
What Does a Software Engineer Do?
A software engineer develops systems and software for businesses and works with users to determine specific software needs, according to Indeed. They design, develop, and test systems or applications, in addition to recommending software upgrades.
As CareerExplorer explains:
“A software engineer applies mathematical analysis and the principles of computer science in order to design and develop computer software. Software engineering is a branch of computer science that includes the development and building of computer systems software and applications software.”
Data Science vs. Software Engineering Comparison Table
Let’s take a quick look at the similarities and differences between these two popular roles:
| Data Scientist | Software Engineer | |
| Main Career Focus | Data-centered position that uses data to create an impact | Develops systems and software for businesses and organizations |
| Skills Required | Math and statistics, programming, data visualization, data compilation, basic machine learning skills, predictive modeling, good communication | Math, science, engineer, and design techniques, strong analytical and problem-solving skills, good communication, programming, and coding languages |
| Education Requirements | An advanced degree is typically required | A bachelor’s degree in a related field; an advanced degree is not typically required |
| Salary Range | $105,000–$165,000 | $64,840–$174,660 |
| Career Outlook | Career outlook for positions are expected to grow 22% between 2020 and 2030 | |
| Companies Hiring for These Roles | Fidelity Investments, Booz Allen Hamilton, Amazon, Microsoft, NASA Jet Propulsion Laboratory, The New York Times | DoorDash, Saks Fifth Avenue, Netflix, Amazon, Adobe, Capital One |
Sources: LinkedIn, the U.S. Bureau of Labor Statistics, Monster, the University of San Diego and ComputerScience.org.
Main Career Focus
A data scientist is a data-centered position that uses data to create an impact. This position works with data to generate valuable business insights and solve real-world problems. A software engineer, on the other hand, works closely developing systems and software for businesses and organizations and applies engineering concepts to software development, as explained by Career Karma.
Skills Required
The skills required for both positions do overlap, specifically when it comes to knowledge of mathematics and statistics, programming and soft skills such as good communication and the ability to effectively problem solve. But there are some distinct differences, as outlined below:
Data Scientist Skills
Compiled from KDnuggets:
- Mathematics and statistics
- Programming (Python and R)
- Data wrangling and preprocessing skills
- Data visualization
- Good communication, being a lifelong learner, team player, business acumen, ethical skills
Other skills commonly deployed by data scientists include machine learning, predictive modeling, data visualization, text mining, programming (including Python, R, SQL, Spark, Hadoop, Julia), and many more. Data scientists also need soft skills, especially oral and written communication, to present often complex concepts to stakeholders.
Software Engineer Skills
Compiled from LiveAbout:
- Math, science, engineering, and design techniques
- Strong analytical and problem-solving skills
- Strong communication and interpersonal skills
- Experience in various programming languages
- Fluency in one (or more) computer coding languages
- Multi-tasking, team player, strong attention to detail
Education Requirements
When it comes to advanced education, a master’s degree is considered invaluable (if not essential) with the majority of data scientist positions requiring an advanced degree. A software engineer, on the other hand, typically needs a bachelor’s degree in a related field (such as computer science) and strong programming skills. Internships are highly recommended, according to LiveAbout.
Salary Range
The outlook for all types of data-related jobs is extremely promising. According to the U.S. Bureau of Labor Statistics, management analysts earned an average of $93,000 in The salary for each position will depend on the specific job responsibilities, how much experience is required, location of the job itself and several other factors. But to give you an idea, here are some average salary ranges for each position:
Data Scientists
- Median annual salary of $100,910 (U.S. Bureau of Labor Statistics)
- National average of $120,306 (Glassdoor)
- Median salary of $98,230 (U.S. News & World Report)
Salary will also increase depending on the experience required and whether there is a supervisory role. For example, a Level 3 Data Science Manager, which typically supervises at least 10 employees, can earn anywhere from $210,000 to $275,000.
>>> Looking for a complete breakdown on data scientist salaries? Learn more about high pay in this exciting, in-demand field.
Software Engineer
- Average base salary of $120,042 (Built In)
- 2021 median pay of $109,020 (U.S. Bureau of Labor Statistics)
- National average of $101,760 (ZipRecruiter)
Career Outlook
The future for both positions is extremely favorable. The job outlook for computer and information research scientists (which include data scientists) is projected to grow 21% from 2021 to 2031, according to the U.S. Bureau of Labor Statistics. Employment for software developers (which includes software engineers) is projected to grow at the same rate during the same time period.
Companies Hiring for These Roles
Since these positions are valued across most industries, you will likely see job postings for both of these positions at the same company. For example, Fidelity Investments, Facebook, and Amazon (among many others) recently listed openings for data scientists and software engineers.
While job postings change every day, here is a snapshot of some top companies that are hiring for both positions:
| Data Scientist | Software Engineer |
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