Omaha Public Power Data Scientist Interview Questions

The questions to prepare for a Omaha Public Power Data Scientist interview. Questions from real interview reports rank first. Updated weekly.

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Handling Missing Values in ML

Easy

Explain practical strategies for handling missing values in a supervised learning workflow, from diagnosis to modeling and validation.

Cross-ValidationFeature EngineeringRegularization

Omaha Public Power

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SQL Second-Highest by Region

Medium

Tests SQL skills for ranking and aggregation on energy consumption data by region.

RankingGroup ByAggregations

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Primary vs Guardrail Metrics

Easy

Explain how a primary metric differs from a guardrail metric and how both are used in A/B test decisions.

ExperimentationGuardrail MetricsA/B Testing

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Statistical Significance of Metric Change

Medium

Tests hypothesis testing, assumptions, and correct interpretation of statistical significance.

Hypothesis TestingStatistical SignificanceP-Values

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Predict Peak Electricity Demand

Hard

Tests end-to-end ML modeling for forecasting peak demand using domain-relevant features.

distributed trainingFeature StoreModel Serving

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Evaluate Imbalanced Model Performance

Medium

Evaluate a model on an imbalanced dataset and judge whether accuracy is misleading.

F1 ScorePrecisionRecall

Omaha Public Power

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