Data Scientist Interview Questions


1. How would you test whether a given dataset follows a normal distribution?
2. Explain the difference between Type I and Type II errors. How do they impact hypothesis testing?
3. You roll two dice. What is the probability that the sum is at least 8?
4. Given a biased coin that lands on heads with probability p, how can you generate a fair coin flip using it?
5. How would you detect and handle outliers in a dataset?
6. How do you deal with an imbalanced dataset in classification problems?
7. Explain how the Gradient Boosting Algorithm works. How is it different from Random Forest?
8. You are given a trained model with poor performance on new data. How would you debug the issue?
9. What is the curse of dimensionality? How do you mitigate its effects?
10. How do you choose the best number of clusters in K-means clustering?
11. Given a table of transactions, write an SQL query to find the top 3 customers with the highest total purchase amount.
12. How would you optimize a slow SQL query that joins multiple large tables?
13. Write an SQL query to calculate the rolling average of sales over the past 7 days.
14. How would you handle NULL values in an SQL dataset when performing aggregations?
15. How would you design a real-time recommendation system for an e-commerce website?

Answering these questions requires an in-depth knowledge of Data Scientist concepts.