I wouldn't say I have a great background in stats and ML. I've never taken a probability theory class in grad school, but some probability theory was covered in my ML class. Is graduate level probability theory knowledge required for interviews, or is an undergrad level sufficient?

The last time I took a pure stats class was back in undergrad, so I definitely need a refresher. I have a pretty strong background in numerical linear algebra, numerical methods, and differential equations (I have NO background in stochastic calculus), but it seems the quant interviews will focus more on the statistical math than the mathematical domains I enumerated.

What would be a good book for me to use to prepare for stats and ML-styled questions?

I've been recommended the following:

Joshi - Quant interview and answer guide

Vault quant interview

Heard on the Street

but I believe all 3 of these are only useful for brainteasers and not for the theoretical stats/ML questions that I may be asked.

Thanks!