C3 AI Interview Questions

This is a data science page more than an engineering one: 6 of C3 AI's 22 questions come from Data Scientist interviews. Two of them are machine learning and statistics recall rather than open-ended modelling. One asks you to name the classic bagging algorithm and say why bootstrap aggregation cuts variance; another pairs a regression error question with a coin-toss expectation, so you need to move between bias-variance and a quick probability calculation without notes. The rest is lighter algorithm work: decompressing an encoded string with nested repeat counts, and finding the longest substring in which every character appears at least k times, which is the divide-and-conquer problem where you split on the rare characters. A restaurant reservation system fills the design slot and one behavioural question closes the loop. Onsite and screening rounds are split almost evenly, at four and three, and the difficulty is mild: 4 medium, 2 easy, one hard. Six of the seven carry a written solution, two are runnable, and none of it sits behind the paywall.