Acudí a una entrevista en Ubiquant Investment (Shanghái, Shanghai)
Entrevista
The interview process began with a thorough resume review, where interviewers delved into my past experiences and projects in detail. This was followed by technical rounds assessing relevant mathematics and statistics knowledge, including probability, linear algebra, and statistical inference concepts. There were also questions on Python programming, covering data structures, algorithms, libraries like NumPy and Pandas, and best practices. The process included live coding tests with practical problems to solve in real-time, focusing on clean, efficient code. Overall, it was rigorous but fair, emphasizing problem-solving skills.
Preguntas de entrevista [1]
Pregunta 1
Can you walk me through the factor design logic in one of the projects listed on your resume? What was your thought process and rationale behind selecting and constructing those factors?
In your resume, you mentioned a trading/investment strategy. Could you explain the core logic and ideas behind it? How did it perform in backtests or live trading (e.g., Sharpe ratio, drawdown, returns)?
How did you validate the factors or strategy in your project? What robustness checks did you perform (e.g., out-of-sample testing, subsample analysis)?
What challenges did you face when implementing the strategy, and how did you address them?
How would you test if a factor has predictive power? What statistical methods would you use?
Explain the difference between in-sample and out-of-sample overfitting in factor models.
How do you handle multicollinearity among factors?
Acudí a una entrevista en Ubiquant Investment (Pekín, Pekín)
Entrevista
HR phone call, on past experience, what the job covers, responsibilities. internal and external connections, requirements, benefits, risk model understanding, strategy understanding, any quant developer experience and so on so forth. location flexible