Tips to Prepare for Data Science Interview Questions and Answers

The ability to extract data insights is becoming increasingly imperative in the complex business environment. That’s why it is getting exceedingly popular to recruit data scientists in business organizations. Besides extracting data, a data scientist performs many responsibilities that extend beyond data and analysis. Communication, testing, and collecting feedbacks are some of the duties of a data scientist that we will discuss in the latter part of the article.

The evolution of technology and the internet has helped companies realize the importance of data in a business milieu. As a result, data has become a vital part of many business organizations. And candidates who used to find it hard to define data science a decade ago and perform tasks like data cleansing and data analysis are able to do the same seamlessly.

Therefore, companies are heavily recruiting data scientists in the present day and age, resulting in increased job opportunities in data science. However, making a career in data science today transcends beyond qualifications and skills. Companies are giving prominence to the persona, personality, and communication skills of aspirants. Thus, to secure a job as a data scientist, you need to work on your oratory skills and brush up on core concepts of data science and analysis.

Below we’ve put together effective tips and tricks on how to prepare for a data science interview. Continue reading to know about the interview preparations one has to undertake to secure a prestigious job.

How to Prepare for a Data Science Interview?

Tip 1: Read and review

The first step you need to undertake while preparing for a data science interview is reading and reviewing all important information regarding your job profile. It could be anything from the job description to responsibilities, qualifications to pay package. Complete knowledge of the prerequisites will aid you while answering some basic data science interview questions like – why is data science important to you, and why do you want to join our company, among others.

Tip 2: Conduct research about the company

The second step in ‘how to prepare for a data science interview’ is conducting research about the company. It is imperative to know about the company for which you are giving the interview beforehand. Understanding a company’s vision, mission, objective, and goals help formulate answers for personality and behavioural-based interview questions ahead of time. In addition, you can refer to websites, newspaper articles, and magazine interviews to gauge the important details regarding the company.

Tip 3: Look for past interview questions

Recruiters often ask technical questions in the interview to test your skills and knowledge about different data science processes. You can refer to technical questions listed on online websites. Read the commonly asked interview questions and try to answer them beforehand. Here are some commonly asked interview questions:

  1. What is linear regression?
  2. What are the different types of programming languages widely used in businesses?
  3. What is data cleaning, and why is it important?
  4. What is the difference between data modelling and design?
  5. How is supervised learning different from unsupervised learning?

Tip 4: Mock interview

A mock interview is the emulation of the original interview process. Pre-planning your interview round before its occurrence helps you gauge what to expect. Practice asking questions, answering technical questions, working on the postures and gestures during the interview, and other things in the mock interview.

Tip 5: Practice

A data scientist works on numerous software. To test your technical capabilities, recruiters might ask you questions pertaining to different software. Therefore, practice the skills you will be tested on beforehand. Study the core concepts of data science, brush up on software like SQL and others, solve case studies, etc.

Here are some of the software and data science system that employees widely use in their daily life. Have a look at them:

  • SQL server
  • Python
  • Data cleansing
  • Data analysis
  • Data mining
  • Data visualization
  • Machine learning
  • Artificial intelligence
  • SAS
  • Apache Spark

On a normal day, a data scientist designs and monitors the data modelling process, creates new algorithms, conducts predictive analysis, extracts data for business purposes, analyzes data and shares it with the stakeholders and business leaders. However, a data scientist performs a varied set of responsibilities, which we’ll discuss in detail in the next section of the article.

Data Scientist Roles and Responsibilities?

  • Extract data, analyze them and draw inferences to arrive at insightful conclusions.
  • Develop different data models and perform data cleansing activities.
  • Use techniques like artificial intelligence, machine learning, and predictive analysis to automate data analysis processes.
  • Perform data investigation and exploratory data analysis.
  • Communicate data-related results and conclusions to stakeholders and brand leaders.

Besides the above-mentioned interesting data scientist’s responsibilities, innovation and creativity make data science one of the desirable career choices. High salary packages and future scope adds to the benefits of developing a career in data science. Besides data scientist, here are some of the popular job roles within the data science industry:

  • Data analyst: Work with large data sets to identify patterns, trends, and meanings.
  • Data engineers: Ease the data scientist’s work by cleaning and grouping data.
  • Data architects: Create and design the data architecture of a company.
  • Business analyst: Work on increasing the efficiency of the data science and analysis processes.
  • Data visualizer: Someone who arranges data in charts, images, and graphs to make it easy to perform analysis.

If you plan to make a career in data science, the job titles mentioned above will help you secure a prestigious job and competitive pay package. Since the demand for data science professionals is high, getting equipped with a set of extra skills will give you an edge over others. But, how to prepare for a data scientist interview? How to prepare for a data scientist job?

You can take up different certification courses for the same, such as Emeritus India’s data science certification course. We offer such courses in partnership with renowned Indian and international education institutes, assisting you in the process of getting your dream job. Enrol yourself on the data science certification course to develop a relevant skillset and gain complete knowledge about the subject.

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