It's interesting to see this, I want to know about how others work.
But I've found with jupyter that it's most productive for me to just use jupyterlab in the browser, it has lots of features and for the visualizations that I do I need a good viewer. So vim doesn't work, and executing in ipython is like the console, not the notebook interface anyway.
I recommend using jupytext too, and then you can keep .py files as the canonical notebook files in your repo and code history.
From my perspective when I had to turn ML models from a "real scientist" to something I could use in production, emacs-ipython-notebooks[1] was immensely helpful for me, since it allowed to connect to the jupyter server and edit and copy things from emacs to other code places as if I'm looking at an org mode file.
I see the appeal of Jupyter notebooks for someone testing out things or experimenting, but it's a bit like a brain dump that isn't that trivial to navigate around when a second or third person is involved.