gsa | | Interview Experience
Interview Date: Not specified
Result: Not specified
Difficulty: Not specified
Interview Process
The interview consisted of back-to-back sessions. The first interviewer asked a Monte Carlo question involving two distributions and inquired about the best algorithm to estimate P(X<Y). The candidate initially focused on improving convergence speed but later realized the emphasis was on reducing variance. This segment lasted around 30 minutes.
The second interviewer, who had a background from Cambridge, began with a thorough review of the candidate’s resume. The first question involved transforming a standard normal variable X ~ N(0,1) to obtain Y ~ N(0,1) such that the correlation between X and Y equals a specified value. The candidate responded with the classic Cholesky decomposition method.
Next, the interviewer posed a question about two independent standard normal variables, X and Y, asking for P(Y > 3X | X > 0, Y > 0). The candidate struggled with this question, particularly in understanding the area calculation, which was clarified by the interviewer using a uniform distribution example.
Finally, the candidate addressed a LeetCode coin problem, providing a quick answer but noted that it was not bug-free. A follow-up question required proving that O(n + k) was not feasible. After some thought, the candidate illustrated a tree structure to explain their reasoning, acknowledging that linear time complexity was unlikely.
The interview concluded with brief small talk before the interviewer abruptly ended the call.
Technical Questions
- Monte Carlo Method
- Normal Distribution
- Coin Change Problem
Tips & Insights
- Focus on understanding the fundamental concepts behind statistical methods.
- Practice explaining your thought process clearly during problem-solving.
- Be prepared for follow-up questions that require deeper insights into your answers.