Python because that's what your team knows. If they aren't already they probably should use Jupyter, pandas, numpy, ... Then sprinkle it with a bit of Haskell

Python because that's what your team knows. If they aren't already they probably should use Jupyter, pandas, numpy, ... Then sprinkle it with a bit of Haskell on the stable algorithms for speed and correctness reasons. Haskell has fantastic abstraction and testing capabilities. Go is probably not going to sit well with data scientists due to the lack of generics. It's a good language for API and CLI but not so much for developing generic algorithms.