Algorithms and data structures are considered core skills for software engineers. How useful are these skills for data scientists and analysts?

A typical data scientist spends most of their time in high-level languages such as Python/R/SQL and rarely needs to think about underlying implementations. This is due to fact that the majority of data analysis and machine learning algorithms are already packaged in ready-to-use, heavily optimised libraries — such as Scikit-Learn, Numpy, Pandas, and others (R fans have their own tools).

To answer the question if algorithms and data structures are worth your time, I will list a few tools…