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Interview Questions

Review this list of 4,477 interview questions and answers verified by hiring managers and candidates.
  • Goldman Sachs logoAsked at Goldman Sachs 
    1 answer

    "import lombok.*; import org.springframework.boot.CommandLineRunner; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.stereotype.Component; import org.springframework.stereotype.Repository; import org.springframework.stereotype.Service; import java.time.LocalDateTime; import java.util.*; @SpringBootApplication public class LldPracticeApplication { public static void main(String[] args) t"

    Yash G. - "import lombok.*; import org.springframework.boot.CommandLineRunner; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; import org.springframework.stereotype.Component; import org.springframework.stereotype.Repository; import org.springframework.stereotype.Service; import java.time.LocalDateTime; import java.util.*; @SpringBootApplication public class LldPracticeApplication { public static void main(String[] args) t"See full answer

    Engineering Manager
    System Design
    +2 more
  • Coinbase logoAsked at Coinbase 
    2 answers

    "Mock interview 2/3/2025 Google Wallet User Needs (pain points): At physical store: understand the price tag proceed the transaction Audio cue to pick one credit card read the payment machine transaction confirmation (optional) balance hear transaction summary At home: check balance make payment send money receive money understand statement Prioritization Understand the price tag"

    C T. - "Mock interview 2/3/2025 Google Wallet User Needs (pain points): At physical store: understand the price tag proceed the transaction Audio cue to pick one credit card read the payment machine transaction confirmation (optional) balance hear transaction summary At home: check balance make payment send money receive money understand statement Prioritization Understand the price tag"See full answer

    Product Manager
    Product Design
  • Data Analyst
    Behavioral
  • +6

    "Clarifying questions I am assuming the time frame for this question is irrelevant as this is a hypothetical question? : Yes Is IG prioritising the creator side or the viewer side more at the moment? : What do you think? I think it should be a balance for the long term sustenance of the network Are all these reels and views in a particular geography or globally? : Globally What is the duration for which these Views are measured? Assume a day Do we know anything about other engagemen"

    Kartikeya N. - "Clarifying questions I am assuming the time frame for this question is irrelevant as this is a hypothetical question? : Yes Is IG prioritising the creator side or the viewer side more at the moment? : What do you think? I think it should be a balance for the long term sustenance of the network Are all these reels and views in a particular geography or globally? : Globally What is the duration for which these Views are measured? Assume a day Do we know anything about other engagemen"See full answer

    Product Manager
    Analytical
    +1 more
  • "I got it right"

    Rudransh V. - "I got it right"See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
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  • Electronic Arts logoAsked at Electronic Arts 
    Add answer
    Product Manager
    Product Strategy
  • Electronic Arts logoAsked at Electronic Arts 
    1 answer

    "Ada Lovelace. There is much to admire about her: her strict analytical thinking coupled with the spirit of creative vision, which recognized a possibility for computers to do more than simply calculate at a time when it was considered revolutionary. Her ability to bridge between disciplines and see the connections between maths and science and even to poetry resonates within me. I also appreciate how she pursued intellectual passions in the face of huge gender barriers in her time."

    Ashish B. - "Ada Lovelace. There is much to admire about her: her strict analytical thinking coupled with the spirit of creative vision, which recognized a possibility for computers to do more than simply calculate at a time when it was considered revolutionary. Her ability to bridge between disciplines and see the connections between maths and science and even to poetry resonates within me. I also appreciate how she pursued intellectual passions in the face of huge gender barriers in her time."See full answer

    Product Manager
    Behavioral
  • Amazon logoAsked at Amazon 
    Add answer
    Software Engineer
    System Design
  • Add answer
    Video answer for 'Design a data warehouse schema for Spotify.'
    Data Engineer
    Data Modeling
  • Add answer
    Video answer for 'Design an app suggestion system for phones.'
    Machine Learning
    System Design
  • "Apoorva Tai is the best. Wash-off effect can be applied on switchback if 1-hour time-block is persisted with, where the first 10-15 minutes of a switchback is ignored"

    Aman M. - "Apoorva Tai is the best. Wash-off effect can be applied on switchback if 1-hour time-block is persisted with, where the first 10-15 minutes of a switchback is ignored"See full answer

    Statistics & Experimentation
  • Statistics & Experimentation
  • Stripe logoAsked at Stripe 
    Add answer
    Video answer for 'Design an application performance monitoring system.'
    Engineering Manager
    System Design
  • +1

    "there's no audio the last ~10 minutes from the interviewer so we can't get a sense of the feedback from the interviewer. I did think it took the interviewee a little too long to figure out the issue itself and could have benefited from taking some time to think and gather thoughts before jumping into drivers of the issue."

    Sabi M. - "there's no audio the last ~10 minutes from the interviewer so we can't get a sense of the feedback from the interviewer. I did think it took the interviewee a little too long to figure out the issue itself and could have benefited from taking some time to think and gather thoughts before jumping into drivers of the issue."See full answer

    Analytical
    Execution
  • "R² → goodness of fit (but can mislead) Adjusted R² → better for model comparison Multicollinearity → hurts interpretability, not always prediction T-test vs F-test → individual vs overall significance Weird case (F not significant, T significant) → likely multicollinearity or instability"

    Dessalew A. - "R² → goodness of fit (but can mislead) Adjusted R² → better for model comparison Multicollinearity → hurts interpretability, not always prediction T-test vs F-test → individual vs overall significance Weird case (F not significant, T significant) → likely multicollinearity or instability"See full answer

    Statistics & Experimentation
  • Add answer
    Video answer for 'What assumptions does the t-test make?'
    Statistics & Experimentation
  • 6 answers
    Video answer for 'What are outliers and how do you detect and handle them?'
    +3

    "Outliers are data points that significantly deviate from the majority of the data distribution. They can arise due to various reasons, such as measurement errors, natural variability, or rare events. Outliers can distort statistical analyses and machine learning models, making it crucial to detect and handle them properly."

    Cesar F. - "Outliers are data points that significantly deviate from the majority of the data distribution. They can arise due to various reasons, such as measurement errors, natural variability, or rare events. Outliers can distort statistical analyses and machine learning models, making it crucial to detect and handle them properly."See full answer

    Statistics & Experimentation
  • +1

    "Use Normalization when: When using pixel values (0-255) into a Neural Network. ➔ Normalize the data between [0,1] to avoid huge input values that could slow down training. When using k-Nearest Neighbors (kNN) or K-Means Clustering. ➔ Because distance metrics like Euclidean distance are highly sensitive to magnitude differences. You are building a Recommender System using Cosine Similarity.➔ Cosine similarity needs data to be unit norm. Use **Sta"

    Abhinav J. - "Use Normalization when: When using pixel values (0-255) into a Neural Network. ➔ Normalize the data between [0,1] to avoid huge input values that could slow down training. When using k-Nearest Neighbors (kNN) or K-Means Clustering. ➔ Because distance metrics like Euclidean distance are highly sensitive to magnitude differences. You are building a Recommender System using Cosine Similarity.➔ Cosine similarity needs data to be unit norm. Use **Sta"See full answer

    Statistics & Experimentation
  • "Netflix is a OTT platform that streams content , TV shows, movies documentaries, to the subscriber's of Netflix. Netflix has approximately 90 million subscribers in USA alone and Netflix's revenue is generated based on their subscriptions. The user buys Netflix subscription, logs in , opens profile and opens the home page of Netflix. 1. Confirmation of the Assumptions Homepage Definition: The homepage is the screen users see after logging into their profile, showing tailored recom"

    Hari priya K. - "Netflix is a OTT platform that streams content , TV shows, movies documentaries, to the subscriber's of Netflix. Netflix has approximately 90 million subscribers in USA alone and Netflix's revenue is generated based on their subscriptions. The user buys Netflix subscription, logs in , opens profile and opens the home page of Netflix. 1. Confirmation of the Assumptions Homepage Definition: The homepage is the screen users see after logging into their profile, showing tailored recom"See full answer

    Product Manager
    Analytical
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