Interview Questions

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Explain precision, recall, and F1-score

Foundational

Machine LearningData Science

Explain what precision, recall, and F1-score mean. When would you optimize for one over the other?

Explain the difference between correlation and causation

Foundational

Statistics & ProbabilityData Science

What's the difference between correlation and causation? Provide examples and explain how you would establish causality in practice.

Explain what a p-value is and how to interpret it

Foundational

Statistics & ProbabilityData Science

What is a p-value and how should it be interpreted in the context of hypothesis testing?

What is feature engineering and why is it important?

Foundational

Data ScienceMachine Learning

Explain feature engineering and provide examples of common feature engineering techniques. Why is it often more important than model selection?

Explain Python list comprehensions and their advantages

Foundational

PythonProgramming

What are list comprehensions in Python? Provide examples and explain when they should be used instead of traditional for loops.

Explain the different types of SQL joins

Foundational

SQLProgrammingData Science

Explain the different types of SQL joins (INNER, LEFT, RIGHT, FULL OUTER) and when you would use each one.

How do you design and analyze an A/B test?

Intermediate

Statistics & ProbabilityData Science

Walk through how you would design, execute, and analyze an A/B test. What are the key considerations and potential pitfalls?

Explain the Central Limit Theorem and its importance

Intermediate

Statistics & ProbabilityData Science

What is the Central Limit Theorem (CLT)? Why is it important in statistics and data science?

Explain cross-validation and its types

Intermediate

Machine LearningData ScienceStatistics & Probability

What is cross-validation? Explain different types of cross-validation and when to use each one.

Explain the bias-variance tradeoff

Intermediate

Machine LearningData ScienceStatistics & Probability

Explain the bias-variance tradeoff in machine learning. How does it relate to model complexity and overfitting/underfitting?

How do you handle imbalanced datasets?

Intermediate

Machine LearningData Science

What is class imbalance? What problems does it cause, and what techniques can you use to address it?

Explain L1 and L2 regularization

Intermediate

Machine LearningData Science

What are L1 and L2 regularization? How do they differ, and when would you use each?

Compare Bayesian and Frequentist approaches to inference

Advanced

Bayesian StatisticsStatistics & ProbabilityData Science

What are the fundamental differences between Bayesian and Frequentist approaches to statistical inference? When would you choose one over the other?