1. Your interviewer didn't give you a good interview or follow guidelines. In interview training they tell you the first thing you must do to start an interview is to ask if the candidate would like to get some water / use the restroom, then break the ice before starting any questions (applicable also during phone screens).
2. Proper interviews actually are supposed to lean heavily toward real-world problem solving approach rather than arcane knowledge. For example, when I interview I look for rational decisions at every turn (not a random example but considering boundary cases, adding a new example to help you visualize the solution should give information gain rather than be something random). My questions are not math oriented, nor do they require deep knowledge of obscure theory. Based on what questions my coworkers ask, I know at least for my team this is not a correct characterization.
What we do test for: understanding of fundamental data structures and algorithms, ability to thrive in uncertainty (ask clarifying questions! state your assumptions!), ability to break a problem down and solve it from first principles.
Good interview questions are required to have multiple solutions.
And then you have the generalization at the end about creativity and diversity; in my limited experience we seem to get pretty decent diversity and even if there is some homogeneity (we need more women and minorities) it's certainly not the kind you described. No, it's not a bunch of mathy theory wizards writing code at Google, it's way more diverse than that. Not perfect, but not awful like you're describing.
1. Your interviewer didn't give you a good interview or follow guidelines. In interview training they tell you the first thing you must do to start an interview is to ask if the candidate would like to get some water / use the restroom, then break the ice before starting any questions (applicable also during phone screens).
2. Proper interviews actually are supposed to lean heavily toward real-world problem solving approach rather than arcane knowledge. For example, when I interview I look for rational decisions at every turn (not a random example but considering boundary cases, adding a new example to help you visualize the solution should give information gain rather than be something random). My questions are not math oriented, nor do they require deep knowledge of obscure theory. Based on what questions my coworkers ask, I know at least for my team this is not a correct characterization.
What we do test for: understanding of fundamental data structures and algorithms, ability to thrive in uncertainty (ask clarifying questions! state your assumptions!), ability to break a problem down and solve it from first principles.
Good interview questions are required to have multiple solutions.
And then you have the generalization at the end about creativity and diversity; in my limited experience we seem to get pretty decent diversity and even if there is some homogeneity (we need more women and minorities) it's certainly not the kind you described. No, it's not a bunch of mathy theory wizards writing code at Google, it's way more diverse than that. Not perfect, but not awful like you're describing.