Catalyst Operations & Analytics Data Scientist Interview Questions
The questions to prepare for a Catalyst Operations & Analytics Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Calculate each Hinge user's 30-day rolling average of daily interactions using CTEs and window functions.
Identify the product KPIs that matter most, connect them to user and business outcomes, and explain the trade-offs behind selecting them.
Identify whether a sudden grid dashboard metric drop reflects a real operational change, data-quality issue, or dashboard defect.
Explain what a p-value means, how it relates to statistical significance, and how to describe it clearly to non-technical stakeholders.
Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
Define a framework to measure whether a new observability dashboard feature is delivering real value and sustained adoption.
Explain what statistical significance means and why it matters when interpreting experimental or analytical results.
Explain how to profile, clean, and standardize missing or dirty data before analysis.
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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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