Fairly involved interview process, though not atypical -- 4 stages that are really 6: - initial high-level recruiter chat - chat with a DS lead, still fairly general - technical interview - 3 x 1hr interviews across case study, leadership and behavioural assessments The process was open-funnel, meaning that there is not necessarily a known and specific vacancy or role that you're orienting toward. Data Scientists from various teams across product, growth, etc. might interview you, and the interview content might not directly map to your particular specialism, though your domain expertise will be taken into account at later stages and when placing you in a team if you're successful. I had a generally good experience with the interviews and tasks themselves, and got to the end of the process feeling positive. No offer unfortunately, and no real problem there: that's the name of the game sometimes. However, there were a couple of aspects that made me wonder how calibrated their use of AI is within their hiring process... For instance, I actually applied directly and had my CV rejected out of hand with an automated response, but was contacted some time later by a recruiter over LinkedIn and invited to interview, which raises questions about their ATS. Additionally the feedback I received after the final round also felt very misaligned with my experience of the interviews, to the point of being actually quite confusing and not representative/irrelevant. My hunch is that, as there were AI notetakers and transcribers on every call, AI is used heavily in the post-interview scoring/write-up process, and the lack of relevant feedback may be an artefact of this. Maybe, maybe not -- potentially something to look into if you're involved in Monzo's hiring.

First stage was a Recruiter Call to discuss salary expectations, role etc Next stage was: Technical Interview SQL Quiz Overall I would say average difficulty, but worth brushing up on interview practise and SQL skills