90min OA, the problems are various and a little bit hard, including machine learning, deep learning, math, algorithm, data processing etc. You can review the pandas and OLS functions if you want to get better results.
I applied online. I interviewed at Qube Research & Technologies (Paris) in Apr 2026
Interview
First round consisted of ML questions. The interviewer was very nice and the interview went pretty well. He told me at the end that he thought I was going to the next round, but unfortunately it has not been the case, not sure why tho.
Interview questions [1]
Question 1
What is XGBoost ? Does the boosting mechanism reduces bias or variance? What is bagging ? What is the architecture of a transformer ? What to do with non-stationary data ? What is important in a ML model beyond the architecture ? What is Adam optimizer ?
I interviewed at Qube Research & Technologies (Hong Kong)
Interview
Introduce myself, Went through two of my resume internships. Then came up with three brain teasers and their extension. The interviewer is friendly but you cannot be wrong in any questions.
Interview questions [1]
Question 1
why you use this model in factor aggregation, do you know the math foundation of it?
I interviewed at Qube Research & Technologies (London, England)
Interview
first interview by quant researcher from QRT. Not including hr interview. Process is good but dont give reason for rejection. Mainly asked questions related to data structure and different model to handle these problem. Asking both Bayesian and time series problem
Interview questions [1]
Question 1
Linear regression model assumptions, list them out