It can, if you have the technical ability to write code that can leverage the scale-out that most bursty-cloud solutions entail. Coding for clustering can be pretty challenging, and I would generally recommend a user target a single large system with job that takes a week over trying to adapt that job to a clustered solution of 100 smaller systems that can complete it in 8 hours.
This is a big part of it. In my lab, I have a lot of grad students who are computational scientists, not computer scientists. The time it will take them to optimize code far exceeds a quick-and-dirty job array on Slurm and then going back to working on the introduction of the paper, or catching up on the literature, or any one of a dozen other things.
