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42 scientist phd interview questions shared by candidates

First phone: two codings (easy leetcode). Also talked about a business problem (short one) and asked a bunch basic ML questions. Second phone: business open-ended: how to build a model to use Uber's data for targeted promotion for Uber eats? On site: First interview, an open-ended business question about a service Uber used to offer called "Instant eat" where a driver would buy a number of meals from a specific restaurant and stay somewhere waiting for users to order food, then deliver them instantly. Asked about advantages/disadvantages? How to model the number of meals need to be bought from a restaurant for a day? Second interview coding. Write a code to get pdf of standard normal distribution and X and returns cdf at X. Basically, doing numerical integration, etc. Third, ML interview. We have two business and residential areas. Build a model to predict the number of ride requests from each area at a time of a day. Fourth, behavior and small questions. Tell me something about yourself that no one knows. Also, some back and forth questions about the business. Fifth, product manager, what do you like about the Uber app? what you don't? If the CEO comes in and tells you we want to increase convenience in apps, how would you tackle this problem? Sixth, going over resume and modeling again. Half going over resume. The other half: we have a queue system for our drivers in an airport, how do you build a model to predict the estimated time of request (wait time for each driver)?
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Data Scientist New PhD

Interviewed at Uber

3.7★
Mar 21, 2021

First phone: two codings (easy leetcode). Also talked about a business problem (short one) and asked a bunch basic ML questions. Second phone: business open-ended: how to build a model to use Uber's data for targeted promotion for Uber eats? On site: First interview, an open-ended business question about a service Uber used to offer called "Instant eat" where a driver would buy a number of meals from a specific restaurant and stay somewhere waiting for users to order food, then deliver them instantly. Asked about advantages/disadvantages? How to model the number of meals need to be bought from a restaurant for a day? Second interview coding. Write a code to get pdf of standard normal distribution and X and returns cdf at X. Basically, doing numerical integration, etc. Third, ML interview. We have two business and residential areas. Build a model to predict the number of ride requests from each area at a time of a day. Fourth, behavior and small questions. Tell me something about yourself that no one knows. Also, some back and forth questions about the business. Fifth, product manager, what do you like about the Uber app? what you don't? If the CEO comes in and tells you we want to increase convenience in apps, how would you tackle this problem? Sixth, going over resume and modeling again. Half going over resume. The other half: we have a queue system for our drivers in an airport, how do you build a model to predict the estimated time of request (wait time for each driver)?

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