Data Scientist vs. Computer Scientist: What’s the Difference?
Taking a dive into what makes a Data Scientist unique from a Computer Scientist
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There’s a lot of confusion out there about the differences between Data Scientists and Computer Scientists.
For one, I’ve seen various job postings say they need a Data Scientist but when looking at the qualifications/requirements it seems a Computer Scientist would be a better fit for the role. The same vice versa.
So what is the difference?
In this article, I’ll try to give you a good idea about the difference between the two by looking at the core principles, skills, how to get started, and salaries of both.
With that being said let’s get started.
Core Principles
Data Scientists
Data science is a relatively new discipline that merges statistics, mathematics, to extract knowledge from a data set by exploring patterns, relationships, and deviations in the data. Data scientists are the most qualified professionals who have skills in all three of these disciplines.
Data science provides a way to use technical expertise for solving real-world problems in various industries including medical, business, research, and engineering. It is a growing field with an increasing number of job opportunities.
Data scientists use computers as their primary tool for analyzing large datasets; they rely on algorithms and statistical models to identify insights or trends which they then communicate back to the stakeholders who requested the analysis.
A Data Scientist needs strong skills in programming languages such as R or Python but also has proficiency with databases like SQL Server or Oracle
Computer Scientists
Computer scientists build the hardware and software that we use today. Computer scientists seek to understand how computers work, and they develop new technologies and find novel uses for computer systems.
Generally, a strong background in mathematics is required as well as an interest or prior experience in coding/programming.
