I write code for a living (data science), but am not really a programmer. So far, my favorite language is Scala with Spark. Other things I've worked with: Pytho

I write code for a living (data science), but am not really a programmer. So far, my favorite language is Scala with Spark. Other things I've worked with: Python, Clojure, Haskell, R, SAS, tons and tons of SQL. The major advantage of functional programming here is that it models the domain really well: the vast majority of my work involves taking a small number of data sets, doing a long sequence of processing, and outputting a small number of data sets. Everything in between benefits substantially from error-preventing techniques such as purity and static types. The biggest disadvantage is how hard it is to analyze and improve performance. Working with Spark means that a pipeline that works on X gb of data will often fail on 5X with out of memory errors, and it's nontrivial to diagnose and fix. It's not clear to me how much of this is due to Spark itself vs. laziness.