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Standard ML is incredibly usable but also very small (syntactically and semantically) especially compared with modern algol-family languages.

There are a couple of quality of life features missing (most notably is record update syntax), but I really enjoy that the core language has not changed in 25 years.

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There is also ongoing discussion and other work on something called "successor ML" (sML). See smlfamily.org for further information. Functional record update is one of the features contemplated.

It's great functional language to learn pattern matching, type inference, polymorphism, etc in an academic setting. Great language to compare and contrast to other languages ( dynamic, OOP, imperative, etc ), but I'm not sure how useful it is as I've never seen it used in the business world. When all you knew was C/C++/Java, standard ml throws you for a loop - in a good way.

At my current job we use Scala extensively. I didn't have much experience with it, but found it pretty easy to pick up, mostly due to its similarity to StandardML (much moreso than e.g. Java, Haskell or Python; which are also clearly influences)

In fact, my only previous experience with Scala was from hacking on Isabelle/HOL, which is mostly StandardML, but happens to use Scala in the periphery (scripting, UI, etc.)!

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