Data vs Applied vs Research Scientist and Coding Proficiency
Been looking at Amazon and Microsoft opportunities, I see these terms being used to describe people working in the general "Data Science" space. From my own research is looks like - Data Scientist = non-PhD, traditional ML - Research Scientist = PhD, more on DL - Applied Scientist = PhD(?), more on DL and has some SWE roles Is this correct? Also, looks like Applied Scientist have coding interview, but the bar is lower than SWE. What about research or data scientist? And is there any difference in these positions/roles between Amazon and Microsoft? Most of my data comes from the Amazon side. Thanks!
What's DL
Deep learning I am guessing
DS: scripting and ML breadth RS: scripting and ML breadth + depth AS: software engineer level 1 and ML breadth + depth
For Facebook, data science/analytics (which is the majority of roles) require no ML at all.
Woah... what do they do then if they don't use ML?
Its more like product analyst, a/b testing and interpretation. In some roles you might be doing simple ML models (~20% of your time)