Data science interview questions

Data Science is among the leading and most popular technologies in the world today. Major organizations are hiring professionals in this field. Demand for data-related professionals like data scientists and analysts has currently outweighed the supply, meaning that companies are willing to pay a premium to fill their open job positions. This article lists the top 10 data science interview questions that might help you get hired in the top companies as a fresher. 

What do you understand about linear regression?

Given the fact that data science involves business and IT, you can also guarantee that you will have multiple interview questions that specifically address the more technical components of the position.

“Linear regression helps in understanding the linear relationship between the dependent and the independent variables. Linear regression is a supervised learning algorithm, which helps in finding the linear relationship between two variables. One is the predictor or the independent variable and the other is the response or the dependent variable”

What is a confusion matrix?

This is the 2nd most important question which is mostly asked by the interviewee. 

“The confusion matrix is a table that is used to estimate the performance of a model. It is a 2X2 table that contains 4 outputs provided by the binary classifier. Various measures, such as error-rate, accuracy, specificity, sensitivity, precision and recall are derived from it”.

How do you check for data quality?

This is another common interview question when any type of data collection or analysis is involved. 

Some of the definitions used to check for data quality are:

Completeness

Consistency

Uniqueness

Integrity

Conformity

Accuracy 

What is Hadoop, and why should you care?

This is a technical question that is mostly asked by the interviewer. 

“Hadoop is an open-source processing framework that manages data processing and storage for big data applications running on pooled systems. Apache Hadoop is a collection of open-source utility software that makes it easy to use a network of multiple computers to solve problems involving large amounts of data and computation. It provides a software framework for distributed storage and big data processing using the MapReduce programming model”.

Explain what resampling methods are and why they’re useful.

Being able to give specific and practical examples of how you might analyze data will be an integral part of the interview for a data analyst position. Be sure to study up on various methods of data collection and their advantages and disadvantages:

“Resampling is used in statistics and can refer to a variety of different methods for validating models by using random subsets, estimating the precision of sample statistics, or exchanging labels on data points when performing significance tests. Resampling is useful to test hypotheses and build confidence intervals when analyzing data.”

What is selection bias, why is it important, and how can you avoid it?

This is another common interview question when any type of data collection or analysis is involved. Your interviewer will be checking your general knowledge about the topic but also your personal opinions about it:

“Selection bias refers to the bias that results from a non-random population sample. This is important to avoid because when collecting data, you want to ensure it’s completely random to properly represent the general population versus a specific group. When strictly avoiding it is impractical, you can use techniques like resampling, boosting, and weighting.”

What is k-fold cross-validation?

In k-fold cross-validation, we divide the dataset into k equal parts. After this, we loop over the entire dataset k times. In each iteration of the loop, one of the k parts is used for testing, and the other k − 1 parts are used for training. Using k-fold cross-validation, each one of the k parts of the dataset ends up being used for training and testing purposes.

Explain how a recommender system works.

A recommender system is a system that many consumer-facing, content-driven, online platforms employ to generate recommendations for users from a library of available content. These systems generate recommendations based on what they know about the users’ tastes from their activities on the platform.

What is ‘fsck’?

This is among the important data science interview questions and you must prepare for the related terminologies as well.

“‘fsck ‘ is an abbreviation for ‘ file system check.’ It is a type of command that searches for possible errors in the file. fsck generates a summary report, which lists the file system’s overall health and sends it to the Hadoop distributed file system”.

Why is R used in Data Visualization?

R is used in data visualization as it has many inbuilt functions and libraries that help in data visualizations. These libraries include ggplot2, leaflet, lattice, etc. R helps in exploratory data analysis as well as feature engineering. Using R, almost any type of graph can be created. Customizing graphics is easier in R than using python.

Apart from these, you will get questions like “Tell me a little about yourself, What motivates you, What can you bring to this role that you’re certain other applicants cannot?”. All these are behavioral interview questions through which they try to find out what got you interested in becoming a data analyst as well as get some insights into your personality.