Me postulé a través de un reclutador. El proceso tomó 4 semanas. Acudí a una entrevista en Jump Trading
Entrevista
Started with a first round interview with a couple of probability/EV problems and coding questions. Then an onsite split into coding, math, data science, and a pretty informal behavioral round. Also got to chat with a couple of folks during the process, which was cool.
Preguntas de entrevista [1]
Pregunta 1
Coding was not really leetcode-style, more just problem-solving and implementing things creatively (more enjoyable imo). Deep knowledge of data structures is definitely helpful. Math stuff was brainteasers/probability questions - definitely pretty difficult, they're more concerned with the approach/thought process than an exact solution. Data science was just testing basic ML knowledge + implementation, understanding pitfalls/tradeoffs of your data.
Me postulé a través de un reclutador. El proceso tomó 4 semanas. Acudí a una entrevista en Jump Trading (Hong Kong) en mar 2026
Entrevista
Few Hr calls prior and between.
First round: Probability questions, questions on general ml knowledge: lasso, ridge, mathematical justification of gradient descent, prob inequalities, linear algebra and geometric interpretations of probability. Final Onsite: Leetcode problems, stats, harder probability problems, deeper into ml knowledge: linear regression basics, pca, linear algebra, questions on the classes you have taken.
ML knowledge is very much needed.
Acudí a una entrevista en Jump Trading (Hong Kong)
Entrevista
interviewed with low-mid frequency equity team.
1st round: coding + statistics, mainly probability, stochastics and OLS. Questions are quite interesting.
2nd round: only about past experience, focus on all the details.
3rd round: onsite interview.
Well organized process: first round covered resume walkthrough, probability, and combinatorics. Final round included deeper probability questions, a data interview, and an HR discussion. Overall, a structured and positive experience.