Interview Questions

Review this list of 3,939 interview questions and answers verified by hiring managers and candidates.
  • Meta (Facebook) logoAsked at Meta (Facebook) 

    "Clarifying Questions: Are we looking to create a product for creators or the end users? - Creators What kind of product are we looking to build? (App /Website/Embedded within the Instagram product ) - Embedded within the app Why do we want to enter the edtech market? (Anything specific insight we have gained which we want to solve for?) - The creator's market is growing substantially and people want to gain knowledge on how to become successful in it. Are there any money or time con"

    Ankit J. - "Clarifying Questions: Are we looking to create a product for creators or the end users? - Creators What kind of product are we looking to build? (App /Website/Embedded within the Instagram product ) - Embedded within the app Why do we want to enter the edtech market? (Anything specific insight we have gained which we want to solve for?) - The creator's market is growing substantially and people want to gain knowledge on how to become successful in it. Are there any money or time con"See full answer

    Product Manager
    Product Design
  • Meta (Facebook) logoAsked at Meta (Facebook) 
    Product Manager
    Product Design
  • Google logoAsked at Google 

    "Machine learning software engineer interviews at Google are really challenging. The questions are difficult, specific to Google, and they cover a wide range of topics."

    Million D. - "Machine learning software engineer interviews at Google are really challenging. The questions are difficult, specific to Google, and they cover a wide range of topics."See full answer

    Machine Learning Engineer
    System Design
  • DoorDash logoAsked at DoorDash 
    Product Manager
    Product Design
    +1 more
  • Nvidia logoAsked at Nvidia 

    "I started off with developing microservices for the game and then incorporating kafka to make it scalable"

    Kiran M. - "I started off with developing microservices for the game and then incorporating kafka to make it scalable"See full answer

    Software Engineer
    System Design
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  • Robinhood logoAsked at Robinhood 
    Product Manager
    Behavioral
  • Meta (Facebook) logoAsked at Meta (Facebook) 
    Product Manager
    Product Design
  • Meta (Facebook) logoAsked at Meta (Facebook) 
    Product Manager
    Product Design
  • Uber logoAsked at Uber 
    Engineering Manager
    People Management
  • Adobe logoAsked at Adobe 
    Software Engineer
    System Design
  • Meta (Facebook) logoAsked at Meta (Facebook) 

    "GAME Goals User Actions (detailed user journey) Metrics - NSM, Secondary, Counter Evaluate"

    Meagan R. - "GAME Goals User Actions (detailed user journey) Metrics - NSM, Secondary, Counter Evaluate"See full answer

    Product Manager
    Analytical
  • "Collaborate with the team to determine which team's product will move the needle the most in achieving the strategic goals and prioritize that work."

    Meagan R. - "Collaborate with the team to determine which team's product will move the needle the most in achieving the strategic goals and prioritize that work."See full answer

    Product Manager
    Analytical
    +1 more
  • Product Manager
    Product Design
  • Product Manager
    Analytical
  • "As an application support analyst, I once encountered a situation where the business problem wasn’t clearly defined. The client had a general idea of what they wanted, but the specifics such as the workflows, system interactions, and expected outcomes were not clear. To move forward, I collaborated with the business analyst and requested both the business and system use cases to better understand the requirements. Once we had those documents, I presented the refined idea to the client for valida"

    Roob G. - "As an application support analyst, I once encountered a situation where the business problem wasn’t clearly defined. The client had a general idea of what they wanted, but the specifics such as the workflows, system interactions, and expected outcomes were not clear. To move forward, I collaborated with the business analyst and requested both the business and system use cases to better understand the requirements. Once we had those documents, I presented the refined idea to the client for valida"See full answer

    Data Scientist
    Behavioral
  • "Looking into licensing data for users to match with the validity of their plans , to set up reporting okr's and metrics from the ground up and future problem sculpting for future feature additions I developed the metrics from the existing data tables , with uniform interpretation for datasets used across teams, keeping the modifications done in alignment with the requirements of the stakeholders. Hypotheses for licensing metrics was laid out in a defined manner where it was feasible to cherry"

    Aishwarya J. - "Looking into licensing data for users to match with the validity of their plans , to set up reporting okr's and metrics from the ground up and future problem sculpting for future feature additions I developed the metrics from the existing data tables , with uniform interpretation for datasets used across teams, keeping the modifications done in alignment with the requirements of the stakeholders. Hypotheses for licensing metrics was laid out in a defined manner where it was feasible to cherry"See full answer

    Data Scientist
    Behavioral
    +1 more
  • "Analytics as a career route was to problem solve and think out of the box , where I would be able to inculcate a data-driven thinking to finding solutions. Establishing a foundation and end to end analytical methodologies for giving recommendations for actionable outcomes useful for internal and external teams relying on these observations. Learning the procedure of how to source unstructured data and clean, impute, introduce variables to build impactful inferences."

    Aishwarya J. - "Analytics as a career route was to problem solve and think out of the box , where I would be able to inculcate a data-driven thinking to finding solutions. Establishing a foundation and end to end analytical methodologies for giving recommendations for actionable outcomes useful for internal and external teams relying on these observations. Learning the procedure of how to source unstructured data and clean, impute, introduce variables to build impactful inferences."See full answer

    Behavioral
  • "A 25% drop-off rate at sign-up for a new app, especially one from Meta, indicates a significant challenge in onboarding and user retention. To analyze this, consider external, internal, and product-specific factors. Identify Potential Causes: External Factors:Competition: Are other platforms offering a more attractive or simpler signup process? Timing: Is there a recent major event or trend that might be influencing user behavior? User Experience: Is the signup process clunk"

    Ankit kumar S. - "A 25% drop-off rate at sign-up for a new app, especially one from Meta, indicates a significant challenge in onboarding and user retention. To analyze this, consider external, internal, and product-specific factors. Identify Potential Causes: External Factors:Competition: Are other platforms offering a more attractive or simpler signup process? Timing: Is there a recent major event or trend that might be influencing user behavior? User Experience: Is the signup process clunk"See full answer

    Data Analyst
    Data Analysis
    +2 more
  • "To analyze a year-over-year (YoY) slowdown in transactions, you should start by understanding the context, segmenting data, identifying potential drivers, and then formulating actionable recommendations. This involves a structured approach that includes a thorough examination of the data, both internally and externally. Understand the Context: Define "transactions": What specific transactions are being analyzed (e.g., website purchases, in-store purchases, total transactions)? Timeframe: Sp"

    Ankit kumar S. - "To analyze a year-over-year (YoY) slowdown in transactions, you should start by understanding the context, segmenting data, identifying potential drivers, and then formulating actionable recommendations. This involves a structured approach that includes a thorough examination of the data, both internally and externally. Understand the Context: Define "transactions": What specific transactions are being analyzed (e.g., website purchases, in-store purchases, total transactions)? Timeframe: Sp"See full answer

    Data Analyst
    Data Analysis
    +2 more
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