JP Morgan Chase Machine Learning Engineer Interview Questions

Review this list of 9 JP Morgan Chase machine learning engineer interview questions and answers verified by hiring managers and candidates.
  • JP Morgan Chase logoAsked at JP Morgan Chase 
    +82

    "My approach to dealing with difficult stakeholders has always been: Engage - Directly engage with the stakeholder, meet or chat Listen - Listen to what they have to say, patiently. Understand - Understand their POV, even if it is impossible at some times Ask - Ask clarifying questions. Why? When? What? Engage again - Keep them in the loop until there is closure For example, we were in the final stages of a very important, strategic project for our organization. I was leading th"

    Jane D. - "My approach to dealing with difficult stakeholders has always been: Engage - Directly engage with the stakeholder, meet or chat Listen - Listen to what they have to say, patiently. Understand - Understand their POV, even if it is impossible at some times Ask - Ask clarifying questions. Why? When? What? Engage again - Keep them in the loop until there is closure For example, we were in the final stages of a very important, strategic project for our organization. I was leading th"See full answer

    Machine Learning Engineer
    Behavioral
    +8 more
  • JP Morgan Chase logoAsked at JP Morgan Chase 

    "Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."

    Gaston B. - "Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • JP Morgan Chase logoAsked at JP Morgan Chase 
    +9

    "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"

    Kishor J. - "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • JP Morgan Chase logoAsked at JP Morgan Chase 
    Video answer for 'Given stock prices for the next n days, how can you maximize your profit by buying or selling one share per day?'
    +9

    "from typing import List def maxprofitgreedy(stock_prices: List[int]) -> int: l=0 # buying r=1 # selling max_profit=0 while rstock_prices[l]: profit=stockprices[r]-stockprices[l] maxprofit=max(maxprofit,profit) else: l=r r+=1 return max_profit debug your code below print(maxprofitgreedy([7, 1, 5, 3, 6, 4])) `"

    Prajwal M. - "from typing import List def maxprofitgreedy(stock_prices: List[int]) -> int: l=0 # buying r=1 # selling max_profit=0 while rstock_prices[l]: profit=stockprices[r]-stockprices[l] maxprofit=max(maxprofit,profit) else: l=r r+=1 return max_profit debug your code below print(maxprofitgreedy([7, 1, 5, 3, 6, 4])) `"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • "It might not be a good idea to predict stock prices only based on reddit comments. You could create a signal from reddit comments that can indicate "social media interest" and feed it into a ML system (along with other features) that predicts prices. Collecting good data to train the model and evaluating it correctly are going to be huge challenges."

    Satyajit G. - "It might not be a good idea to predict stock prices only based on reddit comments. You could create a signal from reddit comments that can indicate "social media interest" and feed it into a ML system (along with other features) that predicts prices. Collecting good data to train the model and evaluating it correctly are going to be huge challenges."See full answer

    Machine Learning Engineer
    System Design
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  • JP Morgan Chase logoAsked at JP Morgan Chase 
    +37

    "function twoSum(nums, target) { let complements = new Map(); for (let i = 0; i < nums.length; i++) { let diff = target - nums[i]; if (complements.has(diff)) { return [complements.get(diff), i]; } complements.set(nums[i], i); } return []; } console.log(twoSum([2, 7, 11, 15], 9)); `"

    Jean-pierre C. - "function twoSum(nums, target) { let complements = new Map(); for (let i = 0; i < nums.length; i++) { let diff = target - nums[i]; if (complements.has(diff)) { return [complements.get(diff), i]; } complements.set(nums[i], i); } return []; } console.log(twoSum([2, 7, 11, 15], 9)); `"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +5 more
  • JP Morgan Chase logoAsked at JP Morgan Chase 
    +17

    " O(n) time, O(1) space from typing import List def maxsubarraysum(nums: List[int]) -> int: if len(nums) == 0: return 0 maxsum = currsum = nums[0] for i in range(1, len(nums)): currsum = max(currsum + nums[i], nums[i]) maxsum = max(currsum, max_sum) return max_sum debug your code below print(maxsubarraysum([-1, 2, -3, 4])) `"

    Rick E. - " O(n) time, O(1) space from typing import List def maxsubarraysum(nums: List[int]) -> int: if len(nums) == 0: return 0 maxsum = currsum = nums[0] for i in range(1, len(nums)): currsum = max(currsum + nums[i], nums[i]) maxsum = max(currsum, max_sum) return max_sum debug your code below print(maxsubarraysum([-1, 2, -3, 4])) `"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • Machine Learning Engineer
    Concept
  • JP Morgan Chase logoAsked at JP Morgan Chase 
    Machine Learning Engineer
    Concept
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