Getting started as an associate
Linear algebra -I'd say a class or two is probably fine here. You'd want to be comfortable with the basic matrix transformations, but don't want to waste time learning extraneous transforms not necessarily applicable to the job role. Note that I'm taking a leap of faith here about the right amount of experience needed since I'm not in the role myself, but I doubt the 5 different classes where I learned and used linear algebra in different arenas is necessary.
Descriptive and inferential statistics - Being able to look at a problem and propose different mathematical options to solve is huge. This should really be covered by an intro to stats class. I'll also post the statistics with python specialization I'm following on coursera (https://www.coursera.org/learn/inferential-statistical-analysis-python?utm_source=mobile&utm_medium=page_share&utm_content=lih&utm_campaign=card_button)
Machine learning techniques and best practices - currently looking into and am deciding on a sequence between Andrew Ng on coursera or a more direct machine learning in python specialization in data camp.
Python analytics stack such as numpy, pandas, matplotlib, seaborn, sklearn etc.
Familiarity with a cloud data studio of your choice (sagemaker studio, google data sheets, ibm watson studio etc).
Experience with design thinking - I don't have as much experience with the client facing aspects of the job, but being able to work with clients, understand and address their pain points, and even make suggestions/improvements on existing systems is huge. A basic intro would probably suffice here.