Goldman Sachs Bank Data Scientist Interview Questions
The questions to prepare for a Goldman Sachs Bank Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Explain why cross-validation is used to estimate generalization and support model selection and tuning.
Goldman Sachs BankDesign an experiment for a new trading signal or workflow change, including metrics, power, randomization, and launch criteria.
Goldman Sachs BankExplain what a p-value means in hypothesis testing and how it relates to statistical significance.
Goldman Sachs BankApproach for handling missing data in an ML data pipeline, including validation, imputation, and safe downstream consumption.
Goldman Sachs BankOutline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.
Goldman Sachs BankPick the right metrics to evaluate a machine learning model and explain why they fit the problem.
Goldman Sachs BankTests SQL proficiency for aggregation and grouping in financial data contexts.
Goldman Sachs BankIdentify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
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Use RANK to order active RBC accounts by balance within each branch, while excluding non-active and unmatched records.
RBC
Alten NederlandGoldman Sachs BankCalculate daily net cash movement and running balances for Alpaca brokerage accounts using a CTE, subquery, and window function.
AlpacaGoldman Sachs BankCalculate a three-day moving average of active-client revenue using aggregation and SQL window functions.
AArete
MITRE
Glassdoor