Junior Quantitative Analyst Data Analyst Interview Questions

10,227 junior quantitative analyst data analyst interview questions shared by candidates

One of the question: Compare two strings from two arrays of n strings and print 'yes' if they are almost similar and 'no ' if they are not. for example if 1 - 'aaabbb' 2- 'aabb' 1- {a:3 b:3} 2-{a:2 b:2} then they are almost similar if for, a: 3-2=1 and for b= 3-2 =1 such difference is less than 3, so for this example, the results is 'Yes' .
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Quantitative Researcher

Interviewed at AKUNA CAPITAL

4
Jul 18, 2019

One of the question: Compare two strings from two arrays of n strings and print 'yes' if they are almost similar and 'no ' if they are not. for example if 1 - 'aaabbb' 2- 'aabb' 1- {a:3 b:3} 2-{a:2 b:2} then they are almost similar if for, a: 3-2=1 and for b= 3-2 =1 such difference is less than 3, so for this example, the results is 'Yes' .

N coffee chains are competing for market share by a fierce advertising battle. each day a percentage of customers will be convinced to switch from one chain to another. Current market share and daily probability of customer switching is given. If the advertising runs forever, what will be the final distribution of market share? Assumption: N is an integer less than 25, Total market share is 1.0, probability that a customer switches is independent of other customers and days. Example: 2 coffee chains: A and B market share of A: 0.4 market share of B: 0.6 Each day, there is a 0.2 probability that a customer switches from A to B Each day, there is a 0.1 probability that a customer switches from B to A input: market_share=[0.4,0.6], switch_prob = [[.8,.2][.1,.9]] output: [0.3333 0.6667]
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Quantitative Developer

Interviewed at AKUNA CAPITAL

4
Mar 23, 2018

N coffee chains are competing for market share by a fierce advertising battle. each day a percentage of customers will be convinced to switch from one chain to another. Current market share and daily probability of customer switching is given. If the advertising runs forever, what will be the final distribution of market share? Assumption: N is an integer less than 25, Total market share is 1.0, probability that a customer switches is independent of other customers and days. Example: 2 coffee chains: A and B market share of A: 0.4 market share of B: 0.6 Each day, there is a 0.2 probability that a customer switches from A to B Each day, there is a 0.1 probability that a customer switches from B to A input: market_share=[0.4,0.6], switch_prob = [[.8,.2][.1,.9]] output: [0.3333 0.6667]

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