AIG AI/ML Analyst Interview Questions
The questions to prepare for a AIG AI/ML Analyst interview. Questions from real interview reports rank first. Updated weekly.
Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
AIGExplain a practical framework for feature engineering, from raw data to validated features that improve generalization.
AIGBuild a classifier for a highly imbalanced dataset and choose metrics, sampling, and thresholds that fit the minority class.
AIGExplain how to design and evaluate an A/B test for a product feature, including metrics, MDE, sample size, and guardrails.
AIGExplain common machine learning evaluation metrics and when each is useful.
AIGInvestigate why one customer segment drives most churn and what actions to take.
AIGTests how you translate model metrics into business outcomes for risk and insurance decisions.
AIGTests cross-functional collaboration and execution to achieve measurable outcomes.
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