A quarter of a Data Scientist’s working life often goes something like this: You met with business stakeholders to scope the model and what it should do. You gathered, ingested, explored, and prepped the data. You iteratively built, tested, and tweaked the model.

And then — just when you finally hit the AUC (Area Under the Curve) threshold you had been targeting — you shared it with business stakeholders, and chances are, it wasn’t exactly what they had in mind. So, you started the process over again. And finally, after countless iterations and reviews, your model was ready for production. From there, you worked with the Engineering or the IT team to operationalize the model — whether that meant building an app, integrating into another system, or serving insights to business decision-makers through a chart or graph.

Source: dataconomy.com
Author: Josh Poduska