What are some KPI's you've used to measure your capabilities as a Data Scientist to ensure you're continuously improving over time?
In the same way that a long distance runner looks to lower their mile-time or an Olympic weightlifter tries to boost their dead lift, I'm trying to think of some "true-north" metrics to be more deliberate with my measuring my accelerated learning over the coming months.
Automating and outsourcing your tasks is one way to show improvement. The KPI could be time-to-delivery (for a project) or ROI if easy to measure (cost savings to your company, increased revenue thanks to your algorithm, amount of fraud eliminated, compare to baseline.)
One metric that I like is how many times your code gets integrated into production mode, versus just being a one-time application to solve a one-time business problem. Re-usability, scalability, and robustness of your solutions are important KPI's. Not to mention collaborative work (working with other teams as opposed to just for your boss.)