How to crunch data in python but add to MERN Stack Application
A MERN stack is essentially javascript, so there's a ceiling to the amount of calculation you can realistically do on the backend with a vanilla implementation. 
I would build a native daemon that runs your Python code, place it in a docker container, and choosing your favorite messaging/transportation system to communicate with your backend API. There are plenty of choices there:

Websockets (raw)
Messaging Queue Libraries (IE ZeroMQ)
MongoDB change streams (Since you are using MERN)

So a classic life cycle would of a data crunch event would be:

Issue a rest-ful command to backend API
Backend API issues a message to daemon using your messaging system
Daemon awakes and crunches data
Daemon sends back result via messaging system to rest-ful api
Backend API reads the message back and send result to front-end
I am trying to create a health score system for my company’s clients. There is a lot of data that I am pulling from through my API. I was crunching data through g-scripts but it is taking a really long time, so I thought using Numpy's vectorization would make things much faster. I was thinking of creating a new web application using the MERN stack but I would like to crunch the data using python. Any suggestions on what to do?