Project structures often organically grow to suit people’s needs, leading to different project structures within a team. You can consider yourself lucky if at some point in time you find, or someone in your team finds, a obscure blog post with a somewhat sane structure and enforces it in your team.
Many years ago I stumbled upon ProjectTemplate for R. Since then I’ve tried to get people to use a good project structure. More recently DrivenData (what’s in a name?) released their more generic Cookiecutter Data Science.
The main philosophies of those projects are:
A consistent and well-organized structure allows people to collaborate more easily.
Your analyses should be reproducible and your structure should enable that.
A projects starts from raw data that should never be edited; consider raw data immutable and only edit derived sources.
This is a set of prescriptions and focuses on the phase before the project actually kicks off.