Beginner's Guide: Top 24 Job Interview Questions for Data Science
Data science interview questions can be tricky. During the data-scientist job interview, you may be asked questions about statistics, programming, data analysis, data pre-processing and modeling.
Consider focusing your job-interview prep on these top 24 common data science job interview questions:
- What is logistic regression?
- Why do we need evaluation metrics?
- How is data science different from traditional application programming?
- What is the difference between supervised and unsupervised learning?
- What is a decision tree?
- What is cross-validation?
- What is a normal distribution?
- What is a random forest algorithm?
- What are univariate, bivariate and multivariate analyses?
- How can we handle missing data?
- What is the benefit of dimensionality reduction?
- How can we deal with outliers?
- What is ensemble learning?
- What is the difference between machine learning and deep learning?
- What is the difference between overfitting and underfitting?
- What is regularization, and why is it useful?
- What is selection bias?
- What is the difference between a validation set and a test set?
- What is the difference between regression and classification machine-learning techniques?
- What are artificial neural networks?
- What tools do you plan to use as a data scientist?
- What is natural language processing, and how is it used?
- What is normalization?
- What is the difference between normalization and standardization?
This article was written by Davis David for HackerNoon and was lightly edited and republished with permission.