Interview Questions

Exponent - "This is a Fermi problem — an estimation or approximation problem with limited information and back-of-the-envelope calculations. There's no right answer: interviewers want to understand how you think and how well you can explain your reasoning, rather than what you already know. Recall the formula for Fermi problems: Ask clarifying questions Catalog what you know Make equation(s) Think about edge cases to add to equation **Breakdown components of your equat"See full answer

Exponent - "First, it's important to recognize this type of question as a Fermi question in disguise. We need to estimate the total market size of Dropbox for small and medium-sized businesses, which involves approximating things like the number of SMBs as well as the average revenue per SMB to get to our answer. Luckily, we have a playbook for these kinds of questions. Here's our formula for tackling Fermi questions: Ask clarifying questions Catalog what you know **Make equation(s)"See full answer

Exponent - "This is another Fermi problem — an estimation or approximation problem with limited information and back-of-the-envelope calculations. There's no right answer: interviewers want to understand how you think and how well you can explain your reasoning, rather than what you already know. Recall the formula for Fermi problems: Ask clarifying questions Catalog what you know Make equation(s) Think about edge cases to add to equation **Breakdown components of your"See full answer

Exponent - "This is an Improve a Product question. Let's first go over the Improve a Product formula: Ask clarifying questions Identify users, behaviors, and pain points State product goal Brainstorm small improvements Brainstorm bolder improvements Measure success Summarize Now, let's begin! Ask clarifying questions Before we begin listing off recommendations, it's important you ask questions to ensure you and the interviewer are on the same page"See full answer

Sarlinson C. - "Firstly, I would start researching the problems in the market, figure the audience for my product and then with the correct ideation to launch build the right product with the right team."See full answer

Anonymous Narwhal - "Ability for system to keep in service without much degradation in SLA or adding significant latency."See full answer

Varun G. - "If I launched a feature users love but that isn't driving business value, I'd first validate whether we're measuring the right metrics — then systematically test monetization paths before deciding to scale, pivot, or kill it. Step 1: Diagnose the Gap I'd start by understanding why engagement isn't translating to business impact. The problem usually falls into one of three categories: Wrong user segment: The feature attracts users who don't convert or have low lifetime value **Mis"See full answer

Jr H. - "for one time i was working as a receptionist in a hotel and one of the rooms that the customer needed was not available but rather we had diffrent room with the same quality i had to convince the customer to use the room we had and i would personally transfer him to the room he desires when its available"See full answer

Jet 1. - "`#include using namespace std; void printNumbersTillN(int n){ if(n_==0){ return; } printNumbersTillN(n-1); // go to the end -> reach 1 cout>_n; printNumbersTillN(n); }`"See full answer

Alan T. - "The difference between convex and nonconvex functions lies in their mathematical properties and the implications for optimization problems. Convex Functions:A convex function has a shape where any line segment connecting two points on its graph lies entirely above or on the graph. This property ensures that any local minimum is also a global minimum, making optimization straightforward and reliable. Convex functions are critical in machine learning and optimization tasks because of th"See full answer

Isnadea soraya R. - "untuk mengurutkan daftar angka secara efisien saya akan menggunakan aplikasi pengolah angka yaitu excel dengan rumus rumus untuk mempermudah dan mempercepat pengurutan daftar angka"See full answer

Archana C. - "I was not very confident in my answers. My explanations were round about and I was mostly nervous."See full answer