My interview began with a first round that felt like two parts combined. I was either given a dataframe or asked to do a simple join, then I had to run an EDA pass and perform an OLS regression in Python. I focused on p-values and R-squared, and I had to explain the regression assumptions and residual-style checks as I discussed the results rather than just report the numbers. The second half focused more on the command line. I needed to be comfortable in a Linux terminal with tools such as grep, find, and awk, while explaining what I was doing and why as I coded.
The rest of the process included practical work involving analytics and data handling. I saw regression-related questions again, used bash commands, and completed a pandas-focused section involving data manipulation and finance terminology. The final part focused on forming insights and included a behavioral round.
The technical bar was noticeable, but the process wasn’t chaotic. It felt more like doing the work end to end than solving trick questions. My experience ended without an offer, though it was a coherent test of statistics, tooling, and communicating what the analysis actually meant.
Location: New York, NY. Overall feedback: Neutral. Offer status: No offer.
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