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Nvidia Data Scientist Interview Questions

Review this list of 14 Nvidia Data Scientist interview questions and answers verified by hiring managers and candidates.
  • Nvidia logoAsked at Nvidia 
    44 answers
    +39

    "Was this for an entry level engineer role?"

    Yeshwanth D. - "Was this for an entry level engineer role?"See full answer

    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    126 answers
    Video answer for 'Tell me about yourself.'
    +118

    "As you know, this is the most important question for any interview. Here is a structure I like to follow, Start with 'I'm currently a SDE/PM/TPM etc with XYZ company.... ' Mention how you got into PM/TPM/SDE field (explaining your journey) Mention 1 or 2 accomplishments Mention what you do outside work (blogging, volunteer etc) Share why are you looking for a new role Ask the interviewer if they have any questions or will like to dive deep into any of your experience"

    Bipin R. - "As you know, this is the most important question for any interview. Here is a structure I like to follow, Start with 'I'm currently a SDE/PM/TPM etc with XYZ company.... ' Mention how you got into PM/TPM/SDE field (explaining your journey) Mention 1 or 2 accomplishments Mention what you do outside work (blogging, volunteer etc) Share why are you looking for a new role Ask the interviewer if they have any questions or will like to dive deep into any of your experience"See full answer

    Data Scientist
    Behavioral
    +15 more
  • Nvidia logoAsked at Nvidia 
    70 answers
    +60

    "I follow a variation of the RICE framework when prioritizing how I ship product features. I start by looking at: Reach: Because the customer segmentation across our product portfolio is so similar, I tend to hold a lot of weight on product features that will maximize our customer reach with a minimal LOE. Impact: After establishing which customer segments will benefit from the product feature, I determine the urgency and estimated impact on each customer segment based on customer i"

    Ashley C. - "I follow a variation of the RICE framework when prioritizing how I ship product features. I start by looking at: Reach: Because the customer segmentation across our product portfolio is so similar, I tend to hold a lot of weight on product features that will maximize our customer reach with a minimal LOE. Impact: After establishing which customer segments will benefit from the product feature, I determine the urgency and estimated impact on each customer segment based on customer i"See full answer

    Data Scientist
    Behavioral
    +10 more
  • Nvidia logoAsked at Nvidia 
    31 answers
    +26

    "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"

    Alfred O. - "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"See full answer

    Data Scientist
    Data Structures & Algorithms
    +6 more
  • Nvidia logoAsked at Nvidia 
    11 answers
    +8

    "In my time at Snapp! I was in charge of communicating the product backlog to our CEO. We had a shared Jira board that he had access to and I made specifically for him. One day he saw me in the office and said he doesn’t know anything about our backlog and that’s because I failed to communicate with him. I got upset at first because of the fact that I made the dashboard exclusively for him. But I tried to ask questions to understand his point of view in depth. He then mentioned he doesn't have t"

    Ra R. - "In my time at Snapp! I was in charge of communicating the product backlog to our CEO. We had a shared Jira board that he had access to and I made specifically for him. One day he saw me in the office and said he doesn’t know anything about our backlog and that’s because I failed to communicate with him. I got upset at first because of the fact that I made the dashboard exclusively for him. But I tried to ask questions to understand his point of view in depth. He then mentioned he doesn't have t"See full answer

    Data Scientist
    Behavioral
    +9 more
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  • Nvidia logoAsked at Nvidia 
    16 answers
    Video answer for 'Given an integer array nums and an integer k, return true if nums has a subarray of at least two elements whose sum is a multiple of k.'
    +12

    " def hasgoodsubarray(nums, k): if not nums: return False if k == 0: for i in range(len(nums)): if nums[i] == 0 and nums[i + 1] == 0: return True return False map = {0:-1} sum = 0 for i,val in enumerate(nums): sum += val rem = sum % k if rem in map: if i - map[rem] >= 2: return True else: map[rem] = i return False print(hasgoods"

    Abinash S. - " def hasgoodsubarray(nums, k): if not nums: return False if k == 0: for i in range(len(nums)): if nums[i] == 0 and nums[i + 1] == 0: return True return False map = {0:-1} sum = 0 for i,val in enumerate(nums): sum += val rem = sum % k if rem in map: if i - map[rem] >= 2: return True else: map[rem] = i return False print(hasgoods"See full answer

    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    18 answers
    Video answer for 'Given an nxn grid of 1s and 0s, return the number of islands in the input.'
    +15

    " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "

    Rick E. - " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "See full answer

    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    Add answer
    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    4 answers
    +1

    "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias. Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit. There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"

    Jyoti V. - "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias. Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit. There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"See full answer

    Data Scientist
    Concept
    +2 more
  • Nvidia logoAsked at Nvidia 
    5 answers
    +2

    "Deep Learning is a part of Artificial Intelligence, it's like teaching the machine to think and make decisions on its own. It's like how we teach a child the concept of an apple - it's round, red, has a stem on top. We show them multiple pictures of apples and then they understand and can recognize an apple in future. Similarly, we feed lots of data to the machine, and slowly, it starts learning from that data, and can then make relevant predictions or decisions based on what it has learnt. A co"

    Surbhi G. - "Deep Learning is a part of Artificial Intelligence, it's like teaching the machine to think and make decisions on its own. It's like how we teach a child the concept of an apple - it's round, red, has a stem on top. We show them multiple pictures of apples and then they understand and can recognize an apple in future. Similarly, we feed lots of data to the machine, and slowly, it starts learning from that data, and can then make relevant predictions or decisions based on what it has learnt. A co"See full answer

    Data Scientist
    Concept
    +3 more
  • Nvidia logoAsked at Nvidia 
    Add answer
    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    Add answer
    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    4 answers
    +1

    "static boolean sudokuSolve(char board) { return sudokuSolve(board, 0, 0); } static boolean sudokuSolve(char board, int r, int c) { if(c>=board[0].length) { r=r+1; c=0; } if(r>=board.length) return true; if(boardr=='.') { for(int num=1; num<=9; num++) { boardr=(char)('0' + num); if(isValidPosition(board, r, c)) { if(sudokuSolve(board, r, c+1)) return true; } boardr='.'; } } else { return sudokuSolve(board, r, c+1); } return false; } static boolean isValidPosition(char b"

    Divya R. - "static boolean sudokuSolve(char board) { return sudokuSolve(board, 0, 0); } static boolean sudokuSolve(char board, int r, int c) { if(c>=board[0].length) { r=r+1; c=0; } if(r>=board.length) return true; if(boardr=='.') { for(int num=1; num<=9; num++) { boardr=(char)('0' + num); if(isValidPosition(board, r, c)) { if(sudokuSolve(board, r, c+1)) return true; } boardr='.'; } } else { return sudokuSolve(board, r, c+1); } return false; } static boolean isValidPosition(char b"See full answer

    Data Scientist
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    1 answer

    "I don't have experience working with alot of Biological Scientists. Most of my experience comes with Data Scientists. Described how I used ideation techniques like brainstorming and other creative ways to get people to find common ground. I also mentioned how I like to do survey's before meetings to prompt people and also get unbiased opnions"

    Mark M. - "I don't have experience working with alot of Biological Scientists. Most of my experience comes with Data Scientists. Described how I used ideation techniques like brainstorming and other creative ways to get people to find common ground. I also mentioned how I like to do survey's before meetings to prompt people and also get unbiased opnions"See full answer

    Data Scientist
    Behavioral
    +1 more
Showing 1-14 of 14