Preparing for an Interview: Acing the commonly asked Data Science Questions – Learnxt

Preparing for an Interview: Acing the commonly asked Data Science Questions

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Preparing for an Interview: Acing the commonly asked Data Science Questions

Preparing for a data science interview can be a bit of a task, as there is no specific set of questions to be asked in the interview. An interviewer can throw you off with an unexpected set of the question at any point of time, irrespective of your experience in data science or certificates you possess.
An interviewer will try to test your statistics, programming, and data modelling skills through a variety of questions. These questions are specially designed to check a person’s performance under pressure.
While pursuing a degree in data science, one should start preparing for the interview process. Preparation is the key to success, and starting preparations early will help you ace the interview.
In this article, we will discuss the common questions asked in a data science interview and how you can ace them. But before that, let us have a look at other key points to be considered while going for a data science interview:
Acing the commonly asked Data Science questions:
We have categorised the data science interview questions into six different categories:
Statistics Programming (General, Big Data, Python, R, SQL)
Modelling Behavioural
Culture Fit Problem-Solving
Statistics Interview Questions:
The process through which data scientists take raw data and create predictions and models is called statistical computing. It is challenging to succeed as a data scientist without advanced knowledge of statistics. An interviewer will ask statistics-oriented data science questions and try to explore your understanding of the subject. Prepare yourself well to answer fundamental statistics questions during a data science interview. Some examples of questions asked are:
Programming:
To test your programming skills, the interviewers will ask you to solve programming problems in theory without writing the code. They might also offer whiteboarding exercises to code on the spot for them. Some examples of questions asked are:
Data Modelling:
Using data modelling, data science provides value to a company by turning the raw data into predictive and actionable information. The interviewers will ask questions based on data modelling to unveil the information and knowledge you possess regarding the same. Unable to explain the theories and techniques you used in your respective models will leave a wrong impression on the employers. Some examples of questions asked are:
Past Behaviour:
Behavioural questions reveal an individual’s character and performance, which is why they are favourite to an employer. Employers try to read between the lines and know how a person can affect the rest of the team. These questions help the interviewers understand how individuals react to a situation and what they have learned so far from their experiences.
The behavioural questions can be categorised further as:
Some examples of questions asked are:
Culture Fit:
The employers generally ask these questions to understand the background of a person and evaluate how they can be an excellent fit for the company. They are basically trying to figure out what made you incline towards data science and the company you are interviewing for. Some examples of questions asked are:
Problem-Solving:
To check your problem-solving skills at some point in the interview, an interviewer will throw a data science problem your way. Some examples of questions asked are:
Ace data science with SRM and LEARNXT:
There is no defined best way to ace any interview, especially a data science interview. Hopefully, the questions mentioned above would help you to grab your favourite data science job role in the desired organisation.
If you are willing to pursue data science, you can enroll yourself in the various degree and certificate data science courses offered by the SRM and LEARNXT collaboration. 1800+ hours of learning, Capstone Project, experiential learning through concepts and real-life case studies, and the latest applied data science curriculum aligned with industry requirements will prepare you into a skilled data scientist from the very beginning.
Stay tuned to LEARNXT to know more about commonly asked data science questions.
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