AI Competence Center Data Scientist Interview Questions
The questions to prepare for a AI Competence Center Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Determine sample size and power for a customer survey or experiment, including MDE, guardrails, and a disciplined decision rule.
Design an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.
Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.
Define a success metric for a new feature that captures real user value, not just raw usage.
Explain what statistical significance means and why it matters when interpreting experimental or analytical results.
Calculate each Hinge user's 30-day rolling average of daily interactions using CTEs and window functions.
Assesses metric evaluation approach and criteria for success.
Explain how to handle NULLs, skewed values, and outliers when preparing an analysis dataset using SQL.
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Calculate a three-day moving average of active-client revenue using aggregation and SQL window functions.
AAreteEEvalueserveSShyena Tech YarnsCalculate three-day rolling passenger entry averages for TfL stations using aggregation and window functions.
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