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Interview Questions

Review this list of 4,477 interview questions and answers verified by hiring managers and candidates.
  • Microsoft logoAsked at Microsoft 
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    Product Manager
    Product Design
  • Bolt logoAsked at Bolt 
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    Product Manager
    Product Design
  • Amazon logoAsked at Amazon 
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    Product Marketing Manager
    Behavioral
  • Google logoAsked at Google 
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    Product Manager
    Product Design
  • "North Star - Monthly Recuring Revenue No of new signup churn/retention CAC"

    George P. - "North Star - Monthly Recuring Revenue No of new signup churn/retention CAC"See full answer

    Business Analyst
    Data Analysis
    +2 more
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  • Meta logoAsked at Meta 
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    Product Design
  • Machine Learning Engineer
    Concept
  • Databricks logoAsked at Databricks 
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    Data Engineer
    Data Pipeline Design
  • 1 answer

    "i said there is hashed, clustered, non-clustered"

    Erjan G. - "i said there is hashed, clustered, non-clustered"See full answer

    Data Engineer
    Technical
  • Yelp logoAsked at Yelp 
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    Product Design
    System Design
  • Meta logoAsked at Meta 
    1 answer

    "Clarifying: How many national resources? For example is this a country with a lot of natural resources or very few we want to preserve? How are the other countries? Is there a lot of conflict around the creation of your country? (We will assume everything is perfect and we have unlimited financial resources) Goals: The two main goals of the product as I can see are preservation and enjoyment. Allowing people to enjoy our natural resources and preserving our natural resources. User seg"

    K D. - "Clarifying: How many national resources? For example is this a country with a lot of natural resources or very few we want to preserve? How are the other countries? Is there a lot of conflict around the creation of your country? (We will assume everything is perfect and we have unlimited financial resources) Goals: The two main goals of the product as I can see are preservation and enjoyment. Allowing people to enjoy our natural resources and preserving our natural resources. User seg"See full answer

    Product Manager
    Analytical
    +1 more
  • Product Manager
    Execution
    +2 more
  • Amazon logoAsked at Amazon 
    2 answers

    "That I had not been a PM for a formal ML product. But good models need sound data and my five years of sql writing and ensuring that DWHs and marts had the data they needed for reporting would be very relevant"

    Tony C. - "That I had not been a PM for a formal ML product. But good models need sound data and my five years of sql writing and ensuring that DWHs and marts had the data they needed for reporting would be very relevant"See full answer

    Machine Learning Engineer
    Technical
    +1 more
  • "Is this s shuttle service or the standard uber service? Let's assume the latter. First Uber should gather some data. Find cities similar to Bangalore in several measures that Uber already services. Al bring in cities in India that already are services by Uber, if any. With this in hand, do a multifactoral analysis to try and understand the likely demand in Bangalore. That will help the company understand how many drivers it needs to launch with, so that user expectations for service are met. Hir"

    Lee F. - "Is this s shuttle service or the standard uber service? Let's assume the latter. First Uber should gather some data. Find cities similar to Bangalore in several measures that Uber already services. Al bring in cities in India that already are services by Uber, if any. With this in hand, do a multifactoral analysis to try and understand the likely demand in Bangalore. That will help the company understand how many drivers it needs to launch with, so that user expectations for service are met. Hir"See full answer

    Product Manager
    Analytical
  • Spotify logoAsked at Spotify 
    1 answer

    "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"

    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

    Product Manager
  • 1 answer

    "hash maps work in key value pair. The keys are hashed with a hash algorithm and resulting hashcode(integer) with related value are stored. Accessing a value, removing an element, Searching the hash map: 1) The hash map value can be accessed in O(1) time once you know the key. 2) If the key is not known, the hashmap value can be accessed in O(n) since you have to iterate atleast once. "

    Kavithadevi P. - "hash maps work in key value pair. The keys are hashed with a hash algorithm and resulting hashcode(integer) with related value are stored. Accessing a value, removing an element, Searching the hash map: 1) The hash map value can be accessed in O(1) time once you know the key. 2) If the key is not known, the hashmap value can be accessed in O(n) since you have to iterate atleast once. "See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • 3 answers

    "The solution produces the same result as the 'prescribed solution' yet it does not get accepted In the test results section transcript['year'] = transcript['year'].astype(str) df = pd.pivottable(data = transcript, index = 'studentid', columns = 'year', values = 'yearlygpa', aggfunc = 'mean').resetindex() df = df[(df['2021'] < df['2022']) & (df['2022'] < df['2023'])] df['average_gpa'] = df[['2021', '2022', '2023']].mean(axis=1).round(2) return df "

    Prachi G. - "The solution produces the same result as the 'prescribed solution' yet it does not get accepted In the test results section transcript['year'] = transcript['year'].astype(str) df = pd.pivottable(data = transcript, index = 'studentid', columns = 'year', values = 'yearlygpa', aggfunc = 'mean').resetindex() df = df[(df['2021'] < df['2022']) & (df['2022'] < df['2023'])] df['average_gpa'] = df[['2021', '2022', '2023']].mean(axis=1).round(2) return df "See full answer

    Coding
    Data Analysis
  • Nvidia logoAsked at Nvidia 
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    Software Engineer
    Concept
  • Microsoft logoAsked at Microsoft 
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    Product Manager
    Behavioral
  • Lyft logoAsked at Lyft 
    1 answer

    "Starbucks"

    Dominique H. - "Starbucks"See full answer

    Product Design
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