New York Life Data Scientist Interview Questions
The questions to prepare for a New York Life Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Use monthly aggregation and a three-row window frame to calculate rolling processed-claim averages by New York Life region.
New York LifeSelect five random numbers from a PostgreSQL table using randomized ordering and a row limit.
New York LifeIdentify New York Life policyholders with multiple active policies spanning at least two product lines.
New York LifeBuild a churn model that flags at-risk customers early using behavioral, billing, and support signals.
New York LifeBuild a classifier for a highly imbalanced dataset and choose training and evaluation methods that surface rare positives.
New York LifeExplain what a p-value means, how it relates to statistical significance, and how to describe it clearly to non-technical stakeholders.
New York LifeInvestigate why a key KPI moved the wrong way after a product change and separate signal from noise.
New York LifeExplain what precision and recall mean in classification, and how to interpret the tradeoff between them.
New York LifeDefine the primary metric, guardrails, and power for a customer-facing A/B test before deciding whether to ship.
New York LifeIdentify major online experiment pitfalls and explain how they can bias results in a streaming product A/B test.
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