Entering interview process for Citadel Sector Data Analyst - does anyone have insight into the OA / case / technicals? Interview Query does a good job of describing the number and order of rounds, and there are a few questions on Glassdoor, but not much beyond that. Thanks.
| +134 | Ken Griffin | 78 | 9h |
| +16 | Final round HF process - is it weird to send another idea? | 5 | 7h |
| +9 | Landing HF Summer Analyst Interviews | 2 | 4d |
| +9 | SF HF Roles | 4 | 1d |
| +6 | Next cooked MM? | 1 | 1d |
| +4 | Kinetic Partners? | 1 | 6d |
| +3 | del | 3 | 1d |
| Minimum GPA for Hedgefund Roles? | 3 | 22h |
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Based on the most helpful WSO content, here are some insights into the interview process for a Citadel Sector Data Analyst:
Case Study/Modeling Test:
Technical Questions:
General Interview Structure:
Preparation Tips:
For more detailed preparation, consider looking into resources like the WSO Financial Modeling & Valuation Bootcamp or other interview prep courses available on Wall Street Oasis.
Sources: Citi Superday Sales and Trading Advice, Citadel (Surveyor) Case Study/Modeling Test, Anyone have info on Insight Partners?, Special Situations / Distressed Recruiting, What's the word on Citadel now?
Posted in the wrong thread. sry..
Ignore the bot answer, the interviews for an SDA are much more focused on the data science side - likely to involve coding session interviews where they give you a dataset and get you to tell them about it using pandas etc
Great, that is in line with what I’m reading and have been told. Thank you very much, I appreciate it. Any recommendation on whether to practice with a tilt towards fundamentals (regression, hypothesis testing, etc…) vs fancy ML? I know both are important, just have limited time and want to optimize it.
You should spend 0% of your time on fancy ML
Yeah all that stuff is good to brush up on and be able to talk fluidly about, but even just being quick with basic data manipulation will go a long way in these types of interviews given there's not really scope to go that deep with any analysis - instantly being able to aggregate by a given category, detect outliers, merge dataframes etc
live coding session for SDA?!
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