ABSTRACT
Measuring things is a big part of data science, but measuring the performance of data scientists themselves is a challenge. This chapter looks at four distinct approaches to evaluating a data scientist’s performance: time, throughput, goals, and opinion. Different approaches may fit different situations. An example of using a hybrid approach is also provided.
