Data Science is all about writing shitty code. Most of the time you're just digging for data in a notebook, and then you can write things out proper once you've got something that could work.
I guess we can distinguish between programming and prototyping. Prototyping is more forgiving because it has narrower scope and spans shorter time. Even then, bad habits tend to carry on to the programming part. So better be deliberate about it.