Trexquant Interview Questions
The Interview Experience is a score from 1 star (very negative) to 5 stars (very positive) generated based on the Interview Insights at this company.
The number you see in the middle of the doughnut pie chart is the simple average of these scores. If you hover over the various sections of the donut, you will see the % breakdown of each score given.
The percentile score in the title is calculated across the entire Company Database and uses an adjusted score based on Bayesian Estimates (to account for companies that have few interview insights). Simply put, as a company gets more reviews, the confidence of a "true score" increases so it is pulled closer to its simple average and away from the average of the entire dataset.
- Very Negative
- Negative
- Neutral
- Positive
- Very Positive
The Interview Difficulty is a score ranging from very difficult (red) to very easy (green) generated based on the Interview Insights at this company.
The number you see in the middle of the doughnut pie chart is the simple average of these scores. The higher the number, the more difficult the interviews on average. If you hover over the various sections of the doughnut, you will see the % breakdown of each score given.
The percentile score in the title is calculated across the entire Company Database and uses an adjusted score based on Bayesian Estimates (to account for companies that have few interview insights). Simply put, as a company gets more insights, the confidence of a "true score" increases so it is pulled closer to its simple average and away from the average of the entire data set.
- Very Easy
- Easy
- Average
- Difficult
- Very Difficult
Interviews at Trexquant
Interview Questions & Answers - Trexquant Examples
Summer Analyst – Investment Banking Division Interview - Mergers and Acquisitions
Two days later, I was invited to their NYC office for Superday. The day started with a 30-minute welcome session by HR, followed by two back-to-back 1:1 interviews with VPs—one focused on technicals (walk me through a DCF, explain WACC, how does $10 depreciation affect the three statements), the other on behavioral and deal experience from my resume.
The group case involved analyzing a mock acquisition target in the renewable energy space. We had 45 minutes to build a high-level pitch deck (no slides, just verbal presentation) and present to a director. Team dynamics were observed closely—someone who dominated the discussion got cut, while collaborative candidates advanced.
Final round included a 30-minute Excel test: build a simple LBO model with given assumptions (entry/exit multiples, debt terms, etc.). Had to calculate IRR and MOIC.
Advice: Know your LBO mechanics cold. They care less about perfect Excel formatting and more about logical structure and speed. Also, ask thoughtful questions about deal flow—interviewers lit up when I referenced a recent transaction they’d worked on (I’d done my homework via press releases).
Why did you choose to decline the offer? (optional)
Accepted a competing offer at a bulge bracket with better long-term mobility into private equity.
Quantitative Research New Grad Interview - Quantitative Research
2. Once I passed the screening I was contacted by recruiter. I had my first interview with the same HR which was a mess. She came late plus didnt let me ask any question and would interrupt me saying that it doesnt matter right now ask once you pass the next rounds.
3. Then after 2 weeks I was contacted back for the first technical round. I nailed it honestly. There was a medium level leetcode style problem and a few classic statistical problems.
4. Same day I received the invitation for final round. But suddenly after 2 hours of getting the link the HR called me saying that we changed our mind and we dont want to move further with you. I was also told that I cannot apply to any new grad roles in this cycle.
GAR Interview - Equities
Quant Researcher Interview - Quantitative Research
Quant Researcher Interview - Quantitative Research
Secondly, the HR interview. It is 80% behavioral stuff and a coding problem at the end (leetcode medium). After this, your internal application is forwarded to teams, which gets a response by anywhere a vacancy is available.
Thirdly, you have to interview with the team lead of the team you get selected in. The interview is very broad (hangman solution, finance knowledge, coding, ML/DL basics, anything relevant to your resume can be asked). I could not make it past this stage.
Fourthly, interview with the CEO, Tyger. he asks you basic knowledge and gets to know you personally, if you made it past all the previous stages, you'll do good on this one. The questions are supposed to be basic and also not much of implementation involved.
global alpha researcher Interview
Alpha researcher Interview - Quantitative Research
1- week project, design an algo to play hangman game,
phone interview, about the online test, resume
phone interview, about the project, and brainteasers
You are given a dictionary consisting of 200k words, some of which are 'fake', like 'aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa', or 'bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb'.
You are given jupyter notebook file, containing a framework of your algo, with a trivial solution.
You have only one chance to submit and test your algo on 1000 words, these 1000 words are not in the provided dictionary.
But you can have 100 test out-of-sample.
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