Difference between Data Analyst Interview & Data Scientist Interview

So, while looking through the Data Analyst interview prep course. I saw a question in the experimental design section asking about song recommendation model. I am confused because throughout the data analyst career path, I did not learn anything about machine learning models or recommendation systems. So why in the Data Analyst path, I am seeing interview questions about that? I am trying to create a distinction between data scientist interview questions and a data analyst interview questions. Because recommendation models should be in the data scientist interview, I am not sure why it is listed in the Data Analyst interview. Unless data analysts get tested on that(recommendation models), but if that was the case, why wasn’t that taught in the Data Analyst career path? I am just trying to figure out if I need to learn recommendation models to be a Data Analyst because the analyst I am aspiring to be is the one that use descriptive statistics and summarize past data to find trends, not the machine learning type and that is why I did not do the machine learning specialist path, I did the analytics specialist path.

In my experience with Codeacademy, they cobble together skill paths and career paths from the various individual courses available on Codeacademy, instead of making a specific career path from the ground up.
There are pro’s and con’s to this approach and unfortunately it gets buggy sometimes. Things that a supposed to be in a particular path is not there and things that are not suppose to be there is mysteriously there and feels very out of place.
Thankfully Google and Youtube has a ton of info on Data Science and Data Analytics enabling most people to wade through the confusion.