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Interview Questions

Review this list of 4,415 interview questions and answers verified by hiring managers and candidates.
  • Meta logoAsked at Meta 
    1 answer

    "This is a Design a Product question. For this, we'll want to follow the formula for success: Ask clarifying questions Identify user types, behaviors, and pain points State the goal and use cases List current solutions Improvements / net new solutions Evaluate and select solutions Measure Success Summarize Ask clarifying questions It's important to get clarity on anything unclear. Asking questions also helps us limit scope early on s"

    Exponent - "This is a Design a Product question. For this, we'll want to follow the formula for success: Ask clarifying questions Identify user types, behaviors, and pain points State the goal and use cases List current solutions Improvements / net new solutions Evaluate and select solutions Measure Success Summarize Ask clarifying questions It's important to get clarity on anything unclear. Asking questions also helps us limit scope early on s"See full answer

    Product Manager
    Product Design
  • Bolt logoAsked at Bolt 
    1 answer

    "import re def naturalsortkey(s): Split the string into a list of text and numbers "item10" -> ["item", 10] return [int(text) if text.isdigit() else text.lower() for text in re.split(r'(\d+)', s)] def natural_sort(arr): return sorted(arr, key=naturalsortkey) \# Example Usage data = ["item10", "item2", "item1", "item20", "2nd item", "1st item"] sorteddata = naturalsort(data) print(f"Standard Sort: {sorted(data)}") print(f"Natural Sort: {sorted_data}") "

    Yitayal B. - "import re def naturalsortkey(s): Split the string into a list of text and numbers "item10" -> ["item", 10] return [int(text) if text.isdigit() else text.lower() for text in re.split(r'(\d+)', s)] def natural_sort(arr): return sorted(arr, key=naturalsortkey) \# Example Usage data = ["item10", "item2", "item1", "item20", "2nd item", "1st item"] sorteddata = naturalsort(data) print(f"Standard Sort: {sorted(data)}") print(f"Natural Sort: {sorted_data}") "See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Microsoft logoAsked at Microsoft 
    1 answer

    "T launch the Copilot Plus feature for Surface, follow these steps: Define Value Proposition: Highlight AI-driven enhancements for productivity, creativity, and collaboration tailored to Surface users. Target Audience: Focus on professionals, creators, and students with specific use cases. Product Development: Ensure seamless integration with Surface hardware (touchscreen, Pen) and leverage Azure AI for unique functionalities. Marketing Strategy: Build excitement with teasers, influencer partner"

    Priti S. - "T launch the Copilot Plus feature for Surface, follow these steps: Define Value Proposition: Highlight AI-driven enhancements for productivity, creativity, and collaboration tailored to Surface users. Target Audience: Focus on professionals, creators, and students with specific use cases. Product Development: Ensure seamless integration with Surface hardware (touchscreen, Pen) and leverage Azure AI for unique functionalities. Marketing Strategy: Build excitement with teasers, influencer partner"See full answer

    Technical Program Manager
    Program Sense
  • Apple logoAsked at Apple 
    1 answer

    "focus was on tradeoffs of diff object detection algorithms, data collection and labelling, foundational models, followup: not working well in production, retraining/active learning"

    Ayush B. - "focus was on tradeoffs of diff object detection algorithms, data collection and labelling, foundational models, followup: not working well in production, retraining/active learning"See full answer

    Machine Learning Engineer
    Machine Learning
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  • Palantir logoAsked at Palantir 
    Add answer
    Software Engineer
    Behavioral
  • WhatsApp logoAsked at WhatsApp 
    Add answer
    Technical
  • Beacon logoAsked at Beacon 
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    Product Manager
    Product Design
  • "clarify: paid users, annual subscription user segmentation: levels; active vs dormant; age; regions use cases & pain points solution brainstorm: retention = activation + engagement + resurrection; prioritization of solutions execution"

    Anonymous Salmon - "clarify: paid users, annual subscription user segmentation: levels; active vs dormant; age; regions use cases & pain points solution brainstorm: retention = activation + engagement + resurrection; prioritization of solutions execution"See full answer

    Product Manager
    Analytical
    +1 more
  • New York Times logoAsked at New York Times 
    1 answer

    "input = [ {"topic": 1, "chapter": 1, "section": 1}, {"topic": 2, "chapter": 2, "section": 1}, {"topic": 3, "chapter": 2, "section": 2}, {"topic": 4, "chapter": 1, "section": 1}, {"topic": 5, "chapter": 1, "section": 1}, {"topic": 6, "chapter": 2, "section": 2}, {"topic": 7, "chapter": 2, "section": 2}, {"topic": 8, "chapter": 2, "section": 3}, ] expected_output = [ {'chapter': 1, 'sections': [ {'section': 1, 'topics': [ {'top"

    Anonymous Unicorn - "input = [ {"topic": 1, "chapter": 1, "section": 1}, {"topic": 2, "chapter": 2, "section": 1}, {"topic": 3, "chapter": 2, "section": 2}, {"topic": 4, "chapter": 1, "section": 1}, {"topic": 5, "chapter": 1, "section": 1}, {"topic": 6, "chapter": 2, "section": 2}, {"topic": 7, "chapter": 2, "section": 2}, {"topic": 8, "chapter": 2, "section": 3}, ] expected_output = [ {'chapter': 1, 'sections': [ {'section': 1, 'topics': [ {'top"See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Meta logoAsked at Meta 
    1 answer

    "This is an interesting 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 Okay great. Now that we have the formula, it's time to execute on it! Ask clarifying questions Before we start identifying possible solutions, it's important we ga"

    Exponent - "This is an interesting 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 Okay great. Now that we have the formula, it's time to execute on it! Ask clarifying questions Before we start identifying possible solutions, it's important we ga"See full answer

    Product Manager
    Product Design
  • Visa logoAsked at Visa 
    1 answer

    "An Object Oriented programming deals with data and members. An Object Oriented Programming consumes more memory. An OOPS Consist of bottom-up approach. An OOPS is more secure Than POP. POP. An POP deals with Functions. An POP is less secure compare to OOPS. An POP contains less memory. An POP doesnt contain acess Modifiers."

    Arun G. - "An Object Oriented programming deals with data and members. An Object Oriented Programming consumes more memory. An OOPS Consist of bottom-up approach. An OOPS is more secure Than POP. POP. An POP deals with Functions. An POP is less secure compare to OOPS. An POP contains less memory. An POP doesnt contain acess Modifiers."See full answer

    Software Engineer
    Concept
  • Microsoft logoAsked at Microsoft 
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    Customer Success Manager
    Behavioral
  • Amazon logoAsked at Amazon 
    1 answer

    "Modernizing banking legacy systems and applications The modernization process typically involves moving from mainframe-based legacy platforms to solutions based on cloud and other modern digital technologies"

    Teja G. - "Modernizing banking legacy systems and applications The modernization process typically involves moving from mainframe-based legacy platforms to solutions based on cloud and other modern digital technologies"See full answer

    Solutions Architect
    System Design
  • Age of Learning logoAsked at Age of Learning 
    Add answer
    Product Design
    Technical
  • Product Design
  • "The correct answer as per the interviewer was since we have to exclude in build product engagement metrics and user feedback for the sake of this question, consulting firms/data analytics firms who do market research we rely on that data to determine how useful a competitor's feature is . again this is the answer provided by the interviewer."

    Manas M. - "The correct answer as per the interviewer was since we have to exclude in build product engagement metrics and user feedback for the sake of this question, consulting firms/data analytics firms who do market research we rely on that data to determine how useful a competitor's feature is . again this is the answer provided by the interviewer."See full answer

    Product Manager
    Analytical
  • Adobe logoAsked at Adobe 
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    Product Manager
    Product Strategy
  • 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
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