got a recruiter reach-out for a data scientist / quantitative analyst hybrid role on one of the analytics teams. interviewing in about 3 weeks and trying to figure out what i'm actually walking into. the JD is vague enough to be almost any kind of DS role.
a few specific things i'm trying to figure out: is it mostly stats/ML or more SQL/product analytics? do they do take-homes or is it all live coding? what's the system design component like for a DS role, does it even apply?
if anyone has done a bloomberg data or quant loop in the last year and can share details i'd really appreciate it. role level would be equivalent to L4-L5 somewhere else.
3 replies
ml_mike
did a bloomberg ML interview 8 months ago, different team but overlapping function. it was heavy on stats fundamentals. like, they asked me to walk through how i'd build a regression model and what assumptions i'd check. not 'implement gradient descent from scratch' but more 'prove you actually understand what the model is doing.' no take-home in my loop, all live. system design was present but framed as 'design a pipeline for X data product', not distributed systems whiteboarding.
analyst_ana
bloomberg's analytics teams are pretty SQL-heavy from what i've seen. the quant teams are a different beast entirely. worth clarifying with your recruiter which org you're going into before you over-index on ML prep.
ds_dmitri
that's really helpful, thank you both. i emailed my recruiter to clarify and she said it's the 'analytics solutions' team, which sounds more product analytics than quant. adjusting my prep accordingly.