StoneX Data Scientist Interview Questions
The questions to prepare for a StoneX Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Calculate a three-day moving average of active-client revenue using aggregation and SQL window functions.
Explain which A/B test methods you use, and why, including hypothesis tests and confidence intervals.
Explain how to select, execute, and interpret statistical significance tests for A/B test results.
Define a framework to measure whether a new observability dashboard feature is delivering real value and sustained adoption.
Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.
Determine the sample size needed to detect a meaningful A/B test effect at a chosen significance level and power.
Explain why correlated customer behaviors do not by themselves prove a causal effect, and how you would tell the difference.
Set a clear north star, supporting KPIs, leading indicators, and guardrails for a new product feature.
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Calculate each Hinge user's 30-day rolling average of daily interactions using CTEs and window functions.
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