The definition of Standard deviation is in chapter 1 of Stats 101. https://www.google.com/search?q=standard+deviation&tbm=isch Apparently, asking Stats 101 chapter 1 question of a so called "Data Scientist" is too much of an irrelevant question!

> expect people to have very high Stats skills

Or as you have made apparent, expect people to have ZERO stats skills!

Some of the innumerate activities I have observed in "expert" data scientists and ML engineers who have years of experience without once thinking about sample sizes

1. Using A/B tests to accept the Null hypothesis instead of rejecting it

2. Squandering away 30M $ in annual revenue because they wanted to avoid a situation/meeting in which they might look like they don't understand statistics. This is hilarious because they simply nodded their head as if they understand all the calculations and then simply dropped any other meetings or followups and left 30M $ on the table

3. Not refreshing a key revenue generating model for 18 months because the were "trying to figure out" why the AUC was improving when the performance on "golden set data" was dropping

4. Using thresholding and aggregation to produce poor quality distorted training data of rich perfectly sampled data

5. Trying to use A/B tests to estimate impact even when the control and variant are not independent

All of the above at FAANGS! My coworkers in a non FAANG company were much more sophisticated. These are the kind of candidates a "build recommendations for youtube" interview selects. Template appliers.

The list of stupidities goes on and on! But yeah, none of them think that a basic understanding of statistics is necessary for work. The good thing about Javascript engineers is that they don't have an understanding of Statistics and are aware of it. However the DS/MLEs are unskilled and unaware of it.