Goldman Sachs Data Scientist Interview Questions
The questions to prepare for a Goldman Sachs Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Define a metric framework for evaluating a new feature, from immediate adoption signals to long-term retention impact.
Goldman SachsDefine the right metrics to judge whether a new product feature is successful.
Goldman SachsExplain practical SQL methods for analyzing large datasets, including filtering, aggregation, sampling, and performance-aware query design.
Goldman SachsExplain practical SQL techniques to preserve data integrity when combining multiple data sources.
Goldman SachsCompute daily active users and a 7-day rolling average using a CTE, distinct counts, and window functions.
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Meta ITUse joins, aggregation, and ROW_NUMBER to find the top three Goldman Sachs products by revenue in each category.
Goldman SachsRank the top 3 completed rides per vehicle per day using joins, a CTE, and ROW_NUMBER.
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Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.
Goldman SachsIdentify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
Goldman SachsExplain your approach to model evaluation, including how you choose and interpret metrics for different ML problems.
Goldman SachsTests understanding of hypothesis testing and how it informs data-driven decisions.
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