Digital Turbine Data Scientist Interview Questions
The questions to prepare for a Digital Turbine Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Tests ownership, analytical judgment, and stakeholder communication through an end-to-end data science project.
Tests conflict resolution, stakeholder influence, data-driven communication, and ownership during disagreement with product.
Calculate a three-day moving average of active-client revenue using aggregation and SQL window functions.
Approach for balancing monetization with user experience in a product decision.
Design an experiment to tell whether a new feature improves true retention, not just short-term usage.
Explain what a p-value means, how it relates to statistical significance, and how to describe it clearly to non-technical stakeholders.
Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.
Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
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Calculate each Hinge user's 30-day rolling average of daily interactions using CTEs and window functions.
HingeCCatalyst Operations & AnalyticsAAlight SolutionsCalculate three-day rolling passenger entry averages for TfL stations using aggregation and window functions.
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