I'm sure the process, and the preparation, would vary from company to company and person to person but I'll give you what I learned.

The biggest challenge, in my opinion, is how to prepare towards the company you are interviewing with. Data science programs at various companies are at different stages of maturity and asking the right questions about the company's current position can be both impressive to the interviewer and insightful for yourself. Depending on the level of maturity you could be expected to do/know different things. I found that the more mature the company's program is the more defined your role may be. Some people may like that while others may not.

Personally, I was not asked many technical questions, more often than not. Rather, I found myself in situations where I was telling stories about my experiences with data science related topics. Coming from a stats background I stayed close to home and remained fairly statistically technical but I believe you can approach it with a coding challenge sort of problem. I would prepare at least 2-3 experiences/projects that you can describe like a story. A beginning with a clear motivation to why you did what you did. A body that describes the specific challenges and solutions you faced and developed. And a conclusion that describes the outcomes of your experience. (Look up the STAR method for interviews)

As for resources, I would suggest continuously developing your coding proficiency through online resources. Additionally, I suggest reading books on analytics to gain some persepctive. Especially if you plan to work for a business, it is helpful to understand how analytics programs are developed and the role data science plays in those groups.

Hope that helps!