Getting up to speed on the business logic was arguably the easiest part of my last job where the product was a liquid biopsy. Regardless of industry, you have to learn how to communicate with stakeholders and collect requirements. The existing software being a mess was a much more significant challenge. They also had similar issues on the data science side, where I would argue they did not lean into modern ML nearly enough and instead opted to do the familiar thing.

I think that's generally true of most knowledge domains for anything resembling complex work. Govt, banking, pharma, medical, SaaS all will have a lot of specific requirements that come from deep historical, regulatory or business needs.

I would suggest that the rise of Python is very similar, as it's common in education circles. It's not even that Java as a language is particularly bad, it's how it is used in practice. Though I really do favor C# over Java, there's a similar stigma that comes from the community itself, not the language or it's baseline abilities. And this is a valid criticism.