Machine Learning Engineer Vs Data Scientist
With the development of Artificial Intelligence, there are new job vacancies trending in the market. And its more confusing especially with role machine learning engineer vs. data scientist, primarily because they are both relatively new emerging fields. After, reading different articles, blogs, and watching the video, I just felt to picture out it more clearly with lying differences about them.
Let me start with an analogy. What is the difference between a Writer and a Professor?. We can say both of them know the “rules and grammar” of a language, where one of them is a story-teller while the other is a rigor practitioner of the “rules”.
Data Scientists work on the raw data, analyze it, connect the dots, and tell a story with a different visualization tool. They usually have a broader range of skill-set and may not have too much depth into more than one or two. They are more on the creative side. Like an Artist.
Machine Learning Engineer, on the other hand, is someone who looks at the data as something they have to take in and churn out output in some appropriate form in the most efficient way possible. The skillset needs to be efficient with related to implementation details. There can be a lot of overlap between the two but it is more like A Data Scientist is a Machine Learning Engineer but not the other way round…
