I think that depends on the phd. In biology at least, a lot of the data types and questions seem specific and bespoke, but they are really not. Its often just tabular data you are working with, and you are generating the same models as any other data scientist generates to find significance in tabular data. The only difference is in interpreting the significance of the model output, but the tooling is often the same as in a lot of fields. This is why PhD computational biologists have no problems pivoting into all sorts of distally related industries from pure biology, to data science, to computer science, ad tech, or even management consulting.