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JPMorgan Chase & Co.
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I was interviewed in Aug 2021.
Round duration - 60 Minutes
Round difficulty - Hard
Timings: Early morning 7am (60 mins )
Subsection 1 (30 mins): MCQ round having 30 questions of 11th and 12th Math (complex numbers, trigonometry, calculas), Probability (Expectancy, bayes theorem, other probability question), Coding (Input/Output Question, Time complexity, Stack Push and Pop, Prefix, Postfix).
Subsection 2 (30 mins): 2 Coding Question 1 easy level (Find max in array), other was medium level (Find all the elements in tree which are at same level, where level is depth of smallest path from root to leaf)
Questions were different for each candidate
The idea is to generate all the possible numbers by trying all the possible combinations of indices. We will run two nested loops to generate all numbers and inside the inner loop with we will have to compare the array, we get after swapping with the maximum number we get till this step.
The basic idea is to perform Depth First Search on the given binary Tree and keep track of the current sum and whenever reached the lead node check if the sum becomes equal to the ‘K’ then pick this path, otherwise just backtrack to the previous node and exclude the value of this leaf node from the current sum.
We are here using a helper function that is recursive in nature and i...
Round duration - 30 minutes
Round difficulty - Medium
Interviewer greeted me and told this round is only on Probability.(This was scheduled same day at 3pm)
He asked Following Probability questions:
Q1: What is Random variable?
Q2: What is Sample space?
Q3: What is Conditional Probability? followed by a Numerical on it.
Q4: What is a Normal Distribution?
Q5: What is Bayes theorem? followed by a numerical on it.
Q6: probability of car accident in one hour is 1/4. What is the probability of accident in half hour?
Q7: Two die are thrown, what is the probability of getting multiple of 3.
Q8: There is 10 Black socks in drawer, 10 white socks. What is the minimum number of socks we need to pick out such that we get a pair?
probability of car accident in one hour is 1/4. What is the probability of accident in half hour?
There is 10 Black socks in drawer, 10 white socks. What is the minimum number of socks we need to pick out such that we get a pair?
Round duration - 30 minutes
Round difficulty - Medium
Interviewer greeted me and told this round is only on Basic DSA.(This was scheduled same day at 3:30pm)
He asked Following questions:
Q1: Introduction and Explain your resume?
Q2: What if we have one class (which has array functionality) and other class (stack) which we will inherit from array class what could possibly go wrong here?
Q3: What is Static data member in Classes?
Q4: What is Static member function in Classes? Can static member functions call normal data member of classes?
Q5: you are given a 2D grid, each index has some value associated with it. From Bottom right cornor you need to find a path till Top left cornor where you can get maximum sum of values from index occuring on the path, You can go in Up direction, Left direction or diagonal up-left direction?
I was asked for approach (No coding was done on compiler)
The basic idea to solve this problem is to use recursion. Recursively call function for next row ( row+1,col ) and next column ( row, col+1 ). If the row is equal to M-1 or the column is equal to N-1, then recursion is stopped.
Algorithm:
Round duration - 15 minutes
Round difficulty - Easy
This round happened around 5pm in evening, i got the call from the interviewer to join Zoom call immediately. In this round (it was kind of rapid fire round on DSA,)
Following questions were asked:
Q1: Introduce yourself and explain your resume.
Q2: What is your favorite data structure and why? I said it is Deque, as it is can be helpful in many questions
Q3: Explain what are segment trees. Also give a question were we can use them.
Q4: What are tries, and give one application of tries.
Q5: Given one array you need to give approach to find out all the permutation of the elements in it. (I gave recursive approach)
Q6: Given the same array and value k, you need to tell if sum of subset can be equal to k. (This question is modification of 0/1 Knapsack. I explained the recursive approach)
Interviewer told me to wait for last HR round (I was on cloud 9 after listening to this as it was elimination round)
The idea is to make an array with exactly two occurrences of each element from 1 to N. Then we will generate all possible permutations of this array and check if any permutation is valid or not.
The steps are as follows:
The idea is to generate all possible subsets and check if any of them sums up to ‘K’. This can be done through recursion.
Here is the algorithm:
subsetSumToK(N , K , ARR):
helper(ARR, N, K):
Round duration - 20 Minutes
Round difficulty - Easy
This round happened around 6:30pm in evening, i got the call from the interviewer to join Zoom call immediately. It was HR+(Probability mix round).
He asked me following questions:
Q1: Introduce and explain your resume.
As i was unable to solve 2 probability question in Round 2. The interviewer immediately asked me 2 probability questions back to back.
Q2: What is bayes theorem and a numerical on it.
Q3: If there is a frog which can go one step forward with probability 3/4. and one step backward with 1/4. What is expectancy to reach 7 steps forward.
I was unable to solve the last probability ques. Was on right track almost in end of interview.
2/18 students were selected for intern JPMC(Quant Research @ 1.5Lakhs stipend)
If there is a frog which can go one step forward with probability 3/4. and one step backward with 1/4. What is expectancy to reach 7 steps forward.
Tip 1 : Do Solve Probability questions on Expectancy, Conditional Probability, Bayes theorem and basic 12th level.
Tip 2 : Prepare your Introduction and Be very concise as interviews are of maximum 30 mins each
Tip 3 : Be very communicative and keep trying each question given till end. Never give up!
Tip 1 : Do include Projects with Live link in resume
Tip 2 : Do Choose simple Format of Word, Don't include to much designing
I applied via Recruitment Consulltant and was interviewed in Mar 2024. There were 2 interview rounds.
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BERT is bidirectional, meaning it can look at both left and right context in a sentence. GPT is unidirectional, it can only look at the left context.
BERT uses transformer encoder architecture, while GPT uses transformer decoder architecture.
BERT is pretrained on masked language model and next sentence prediction ta...
Attention mechanism allows models to focus on specific parts of input sequence when making predictions.
Attention mechanism helps models to weigh the importance of different parts of the input sequence.
It is commonly used in sequence-to-sequence models like machine translation.
Examples include Bahdanau Attention and Transformer models.
To deal with skewed distribution of a variable, transformations like log, square root, or box-cox can be applied.
Apply log transformation to reduce right skewness
Apply square root transformation to reduce left skewness
Apply box-cox transformation for a more generalized approach
Consider removing outliers before applying transformations
Python code to determine the least common sub word in a given list with strings
I applied via Recruitment Consulltant and was interviewed in Mar 2024. There were 2 interview rounds.
BERT is bidirectional, GPT is unidirectional. BERT uses transformer encoder, GPT uses transformer decoder.
BERT is bidirectional, meaning it can look at both left and right context in a sentence. GPT is unidirectional, it can only look at the left context.
BERT uses transformer encoder architecture, while GPT uses transformer decoder architecture.
BERT is pretrained on masked language model and next sentence prediction ta...
Attention mechanism allows models to focus on specific parts of input sequence when making predictions.
Attention mechanism helps models to weigh the importance of different parts of the input sequence.
It is commonly used in sequence-to-sequence models like machine translation.
Examples include Bahdanau Attention and Transformer models.
To deal with skewed distribution of a variable, transformations like log, square root, or box-cox can be applied.
Apply log transformation to reduce right skewness
Apply square root transformation to reduce left skewness
Apply box-cox transformation for a more generalized approach
Consider removing outliers before applying transformations
Python code to determine the least common sub word in a given list with strings
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