The Complete Collection of Data Science Interviews – Part 1

The first part covers the list of Behavioral, Situational, Statistics, Python, R, SQL, Data Analytics, and Business Intelligence interview questions.

The Complete Collection of Data Science Interviews – Part 1

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Editor's note: For the full scope of repositories included in this 2 part series, please see The Complete Collection of Data Science Interviews – Part 2.


Were you in the situation when the interviewer asked you a situational or technical question, and you froze up? Just because you were not prepared for it. It happens to many, including me. I have tendencies to freeze during technical interviews, and the hiring manager will take it as my weakness to reject me at the initial stage of the recruitment process. 

To overcome this problem, I started to look at sample interview questions. Let's say the interview is related to a machine learning engineer, and the company is building NLP solutions. I will prepare for basic Statistics, Python, Deep Learning, and NLP interview questions. 

The two-part collection of data science interview questions will help you prepare for all data-related jobs. The collection of interviews is divided into categories based on subject and data field.


Table of Contents


  1. Behavioral Interview Questions
  2. Situational Interview Questions
  3. Statistics Interview Questions
  4. Python Interview Questions
  5. R Interview Questions
  6. SQL Interview Questions
  7. Data Analytics Interview Questions
  8. Business Intelligence Interview Questions


Behavioral Interview Questions


Behavioral Interviews are based on a candidate's experience in relation to skills, abilities, and knowledge. The interviewee will explain how he came over a specific situation in the past. These questions are asked to assess a candidate's ability to adapt, communicate, and overcome problems on a day to day tasks. 


Sample Question: “How would you handle your schedule when it’s interrupted?”



Situational Interview Questions


Situational questions are similar to behavioral questions. Instead of experience, it focuses on future hypothetical scenarios. It is used to assess your ability to handle real scenarios in the workplace. These questions help the hiring manager understand your thought process and ability to solve problems with limited resources.  


Sample Question: “How would you deal with an employee you are managing that is producing work that doesn’t meet expectations?”



Statistics Interview Questions 


Data science is purely based on statistics. You need to explain how a particular algorithm works or how to implement a statistical solution in a respective business during the interview. It is better to go through all of the basic terms and questions.


Sample Question: “What is the difference between Descriptive and Inferential Statistics?”



Python Interview Questions


If you have mentioned Python as your primary language to perform analytics and machine learning tasks, you must know everything about the best coding practices. The interview questions are related to features, data types, functions, creating unit tests, writing clean and production-ready code, and data science use cases. 


Sample Question: “What is the lambda function?”



R Interview Questions


R is a language for statistical analysis. The interview questions are related to the advantages of R over Python, memory management, variables, functions, loops, and building data solutions. Make sure you know the R data libraries and their use cases. 


Sample Question: “Describe how R can be used for predictive analysis?”



SQL Interview Questions


SQL is the mother language for data professionals. I was asked about SQL even in a Deep Learning Engineering job interview. To train a large model, you need to learn to ingest data from multiple databases. SQL is also used for data analytics. Before you appear for an interview, make sure you understand syntax and its functions.


Sample Question: “Describe how R can be used for predictive analysis?”



Data Analytics Interview Questions


For data analytics questions, you need to prepare for business-related problems using modern analytical tools. You need to know data ingestion, data cleaning, exploring and analysis, and interpreting the results. Make sure you are aware of statistical and analytical tools such as SQL, Python, R, Tableau, and Spreadsheet.


Sample Question: “How do you treat outliers in a dataset?”



Business Intelligence Interview Questions


Business Intelligence (BI) plays a vital role in monitoring business performance to provide actionable insights. As a BI analyst, you must understand business processes, monitor KPIs, ability to extract and clean data using SQL, and create dashboards and analytical reports using Tableau or PowerBI. You must be prepared for a case study or BI situational interview.


Sample Question: “ How will you define OLTP (Online Transaction Processing)?”



Final Thoughts


It is summer internship time, and most students are looking to secure internships in top companies. The collection of data science interview questions will help you prepare for all situations and technical questions.

If you are looking for a single source of information, I suggest you read Ace the Data Science Interview book by Nick Singh and Kevin Huo.

In the next part we will cover:

    1. Data Management Interview Questions
    2. Data Engineering Interview Questions
    3. Machine Learning Interview Questions
    4. Deep Learning Interview Questions
    5. Natural Language Processing Interview Questions
    6. MLOps Interview Questions
    7. Cloud Computing Interview Question
    8. AI Manager Interview Questions

This is the 4th edition to data science collection series, check out:

    1. The Complete Collection of Data Science Cheat Sheets – Part 1 and Part 2
    2. The Complete Collection of Data Repositories – Part 1 and Part 2
    3. The Complete Collection of Data Science Books – Part 1 and Part 2

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in Technology Management and a bachelor's degree in Telecommunication Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.