Rackspace Technology Data Scientist Interview Questions
The questions to prepare for a Rackspace Technology Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Design a feature experiment with clear hypotheses, metrics, power, randomization, analysis rules, and safeguards against common pitfalls.
Identify major online experimentation pitfalls and explain practical mitigations for SRM, network effects, peeking, and novelty.
Compute each user's seven-day activity average and compare it with the corresponding rolling average from the prior week.
Choose missing-data strategies that preserve signal and minimize bias in a supervised model.
Explain statistical significance, p-values, practical importance, and uncertainty to a non-technical stakeholder.
Build a systematic process to validate, decompose, and explain a sudden 10% drop in core engagement.
Define a meaningful engagement metric for a retail analytics mobile application and explain how to validate it.
Diagnose a below-expectations product metric drop using decomposition, guardrails, and experiment checks.
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Calculate monthly cohort retention using date-based cohorts, aggregation, and window functions.
XtageBBandhan TechnologiesBBoston Tech IndiaUse aggregation and a window function to rank active players by completed purchase spend, including players with no qualifying purchases.
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