Quantitative Associate Interview Questions

10,163 quantitative associate interview questions shared by candidates

If I give you an array of integers, L, and another integer, s, can you write a program to find out whether there exists a *pair* of integers in L which sum up to s. What's the time complexity of this program? Can you find a faster version? Example: L = [8,4,7,1,4], s = 11. In this case, the program should return true since 7 + 4 = 11.
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Quantitative Analyst

Interviewed at Goldman Sachs

3.7
Oct 1, 2017

If I give you an array of integers, L, and another integer, s, can you write a program to find out whether there exists a *pair* of integers in L which sum up to s. What's the time complexity of this program? Can you find a faster version? Example: L = [8,4,7,1,4], s = 11. In this case, the program should return true since 7 + 4 = 11.

Explain your research. The candidate should be able to understand their own work and explain it to others in a simple way. It is also the time to show the interviewer that your background is a match for the job you are applying for. Probability questions: e.g. there are a total of one hundred strings that each has a length of one inch. If you randomly tie two loose ends up, what is the average length of all strings (expected value)? If you randomly tie 2n loose ends up, what is the average length of all strings? Algorithm questions: e.g. string manipulation (e.g. sorting)
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Quantitative Analyst

Interviewed at Goldman Sachs

3.7
Jul 12, 2018

Explain your research. The candidate should be able to understand their own work and explain it to others in a simple way. It is also the time to show the interviewer that your background is a match for the job you are applying for. Probability questions: e.g. there are a total of one hundred strings that each has a length of one inch. If you randomly tie two loose ends up, what is the average length of all strings (expected value)? If you randomly tie 2n loose ends up, what is the average length of all strings? Algorithm questions: e.g. string manipulation (e.g. sorting)

Round 1: 6 OA problems 40 minutes which had probability and linear algebra. Being familiar with matrix manipulation, Poisson PDF, recursion relations is more than enough. Round 2: 30 min CV review and motivation as to why QR rather than doing research in academia. Next 30 minutes: 4 probability/brain-teaser/linear algebra/market making. The probability/brainteaser problems are of style that are seen in dynamic programming i.e. recursive relation but no live coding was asked.
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Graduate Quantitative Researcher

Interviewed at DRW

4.4
Jul 31, 2025

Round 1: 6 OA problems 40 minutes which had probability and linear algebra. Being familiar with matrix manipulation, Poisson PDF, recursion relations is more than enough. Round 2: 30 min CV review and motivation as to why QR rather than doing research in academia. Next 30 minutes: 4 probability/brain-teaser/linear algebra/market making. The probability/brainteaser problems are of style that are seen in dynamic programming i.e. recursive relation but no live coding was asked.

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