When building programs with user interfaces*, there are parts that _cannot_ be tested formally with either types or automated tests, because they require a human to test how things "feel."
In that context, long compile times lengthen the build-evaluate feedback loop to a point that harms quality.
* also note that APIs are user interfaces. So this harms way more than just programs with GUIs.
Same for data analysis. It is mostly exploratory and iterative work, with the need for a feeback loop (making plots, checking for unusual values, etc.) because the input data is unpredictable.
That's why data scientists prefer interpreted languages and Jupyter Notebooks.
In that context, long compile times lengthen the build-evaluate feedback loop to a point that harms quality.
* also note that APIs are user interfaces. So this harms way more than just programs with GUIs.