Aig Data Scientist Interview Guide

We’ve seen AIG evaluate data scientists with a fairly conventional technical surface, but the candidate experience suggests the bar is less about novelty and more about whether you can operate cleanly at the level you’re claiming. In the one detailed report we have, the candidate moved through conversations with multiple stakeholders, including a senior director of data science, and described the technical portion as smooth and straightforward. That lines up with a process that seems to reward candidates who can answer core modeling questions crisply — even something as basic as Lasso vs. Ridge can be used as a proxy for whether you understand tradeoffs, not just terminology.

What stands out more is the mismatch between how candidates are evaluated and how the offer is ultimately handled. A recurring theme in this account is that the company appeared to assess the candidate as senior throughout, then later tried to down-level the role and reset compensation. That tells us AIG may be highly sensitive to internal leveling and budget constraints, even after technical approval. Our candidates should read that as a signal to make title and scope alignment explicit early, because the real risk here is not failing the interview — it’s discovering late that the company’s idea of the role is narrower than yours.