What does is mean to be a data scientist?
This post addresses the following prompts:
- What do you think being a data scientist is about?
- What do you see as the major duties and/or knowledge areas?
- What differences/similarities do you see between data scientists and statisticians?
- How do you view yourself in relation to these two areas?
Unwrapping what it is that a data scientist does can be confusing when comparing it to other careers, such as a data analyst, a statistician, or a machine learning expert. A data scientist is really a combination of these three things because they need to understand how to run analytics, how to interpret their findings, & how to apply those findings to help answer a question or solve a problem for a business or client. It’s important for a data scientist to be more than just a good programmer, but someone who understands statistics and how to apply that knowledge to the real-world scenario at hand as well.
The job of a data scientist and statistician overlap in many respects; however, the primary difference between them is that a data scientist more often applies their knowledge of statistics using machine learning and programming skills.
Personally, I find myself much more inclined towards a profession as a data scientist because I find work particularly rewarding when it benefits society in some way. The ability to connect with a business or client and potentially help improve their business model would be of great interest to me. I have found the courses I have taken throughout the NCSU Master’s of Statistics program to prepare me to pursue either of these professions.
If you’d like to learn more about this topic, the following articles may be of interest:
Data Scientists Versus Statisticians
Machine Learning Engineer vs. Data Scientist
Data Science vs. Data Analytics vs. Machine Learning: Expert Talk
This is the difference between statistics and data science