Interview Questions

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

Ayushi A. - "total outcomes : 36 total favourable outcomes : 35 probability of favourable outcomes: 35/36"See full answer

Suyash kumar T. - "I will talk about the carwash landscape here a bit. How futuristic do you want the solution to be - flying cars kind of futuristic or something that I can use even now ? What do you mean by a car wash - Is it a physical location where I take my car to OR is it something that I can install at home ? There are two sides to a car wash set up - the car wash company and the user - I am going to assume that we are building this solution for the user. Is there an specific goal in mind or I can cho"See full answer

VictorSage - "The critical data to forecast projects with greater accuracy are Remaining Estimated work, Customer needed date, Cost of Delay."See full answer

Anonymous Muskox - "So Machine learning provides the ability to machines to learn patterns from large data. So applying the same when needed. So the type of algorithm depends on the requirement/use case or the data. For example, if we have data that is labeled and we need to do classification then we will go and perform logistic regression but if we want prediction instead of classification, then we will go and build a regression model. In case the data is not labeled, then we can go ahead and build a model usin"See full answer

1036 loknadh R. - "No ,MSE is suitable for only regression modes. Although the logistic regression in Its name has regression , but it is a classification problem so MSE is not suitable for classification models like logistic regression."See full answer

Exponent - "This is a Technical question. It tests your ability to understand high level technical concepts. Even though your job won't have any coding involved, you'll still need to understand these concepts. Being able to cover all these topics with clarity communicates confidence in your interviewer. Unfortunately, there's no formula for technical questions, but some general tips are: Use analogies when you can Break your solution into clear, bite-size steps Don't be afraid to use examples to b"See full answer

Lucas G. - "Type I error (typically denoted by alpha) is the probability of mistakenly rejecting a true null hypothesis (i.e., We conclude that something significant is happening when there's nothing going on). Type II (typically denoted by beta) error is the probability of failing to reject a false null hypothesis (i.e., we conclude that there's nothing going on when there is something significant happening). The difference is that type I error is a false positive and type II error is a false negative. T"See full answer

Medha A. - "DAU and MAU: The number of active users daily and monthly to gauge the content recommended on the home page. Bounce Rate: The percentage of users who navigate away from the site after viewing only the home page. Number of Signups: The number of users who signup after seeing the content on the homepage leading to lower CAC. "See full answer

Anonymous Muskox - "Metrics which Youtube Consider before building a recommender system Number of likes on a video by user The watch time of a video by the user The video disklied by the user The video share by a user The video skipped or churn with 20-30 seconds. Depending on this Youtube build a recommender system. The video suggestion feature in youtube works based on the recommender system. It may use a hybrid of batch prediction and online prediction. So depending on the above metrics, the youtube p"See full answer

Matthew P. - "I am"See full answer

R - "Assumptions I am going to assume that users know how to send smell through the phone I am also going to assume this is only available between phone-to-phone and not server-to-phone Clarifying questions What are the goals? Customer retention or New market/user acquisition? I would like to pick New Market/User acquisition because this is a new technology that can be used in new use cases in new verticals. Metrics We will measure number of users who used this new technology We will measure"See full answer