Shortly after my application, I was contacted by the Scientific Active Equity team to schedule a phone interview. The process originally included two 30-minute interviews, but finally they informed me that I would be going through one interview with both assessors jointly. The interview itself included almost no competency questions and was mostly about background and relevant skills and how these could be practically applied to the research being carried out at the department. I was also asked about my outlook on global equity markets and the current drivers of growth of asset prices. Overall, I cannot say it was a very difficult interview but since I was expecting something more competency-focused, I was a bit unprepared. I would say there was a big focus on what you could contribute to the department, since they are looking for novel approaches on the problems they face. They seemed very interested in programming skills as well as in a machine learning background as far as I could tell. Also they wanted you to be really specific and explain some things in great detail, especially the technical details concerning relevant projects you have been involved with.

Complete two LeetCode problems. After solving each, record a short video explaining your reasoning, algorithm choice, key trade-offs, and time and space complexities. Focus on clarity, concision, and structured communication.