I like Nick's answer. Could you afford the wonderful CRAY nodes? maybe, but that doesn't mean you should rush into it before you've developed an algorithm and tested it over a cluster. So, if cost/timing is relevant, then a Pi cluster could function as a low-cost testbed to help you work through the project cycle (and reusable).
One thing we might do with a small cluster or large cluster is simply network it with other "heterogeneous" nodes. This just means that you can have many different machines, maybe you add a couple compute nodes with SLI'd GPUs for certain tasks. Some applications would benefit.
Might help to think about what the purpose of the cluster is. General compute? problem specific?
At Disney, there are teams of engineers (applied mathematicians and computer scientists mostly) who devise how and where different pieces of their large puzzle are to be rendered. They have over 100,000 nodes that need to render frames for multiple films in a single year. They've automated the process so that their farm is always being used. If you can build a pi cluster that does enough work for you to survive a year while constantly being under workload (because you've always scheduled rendering tasks), then it might be a very cost effective way to build a cluster. It's only another $100 to add a bit more compute when you have more work to do than your capacity. This is only 1 strategy.
I don't know what the limit of RAM is on one of these. I know the Pi 4 has 4GB option, but I don't have the chops to stick in a bigger stick on one of these boards.