How to Make Progress As A Data Scientist

This post is about what it takes to make progress for your team/company as a data scientist.

Making progress in any professional field, including in data science, is not the same thing as completing tasks. Anyone who has spent at least a couple of years working has probably experienced the feeling of being really busy and yet always just barely keeping up. I would argue that by definition, this state of affairs indicates progress has not been made.

To make progress, one must be able to solve problems in a permanent way. That means that old problems are no longer problems, not for you, and ideally not for anyone else either.

One reason why the tech industry is so different is that software is particularly focused on making progress. Code changes not only fix problems for one person in one situation but have the potential to have solve problems permanently for everyone. When Data Science is done well, it inherits this potential for progress making.