Those titles. What type of roles do they cover? Is there a quick summary -- particularly between analyst and scientist. I expect engineer is source quality, repeatability, accuracy, precision, feature engineering, etc. In other words making the data stable and easily consumed, whether that is directly from the instrument or the charts for the final decision.
The nuance between analyst and scientist is less clear. Can you describe what type of candidates the two draws or what you look for depending on the title?
My job title is currently "Data Engineer" I work in an industrial plant. Here's my two cents:
My background is in Engineering (I'm a materials engineer by qualification). What differentiates me from a statistician, analyst etc is my domain knowledge. I have almost 15 years experience working with industrial processes. I have the background knowledge of chemistry, thermodynamics, mechanics etc. Which someone with a stats background would be lacking. So when I am asked to optimize an industrial process I can utilize that expertise whilst developing models.
I would expect that a data scientist would know more about machine learning and would have a much stronger stats background than me. They'd also probably write much better code (I work in C/C++ and SAS, from what I have seen data scientists tend to be Python/R focused).
Not the OP, but in my experience a "Data analyst" is mostly responsible for writing analytical SQL queries and generating reports. So they don't require a strong math background or programming skills (other than SQL).
The nuance between analyst and scientist is less clear. Can you describe what type of candidates the two draws or what you look for depending on the title?