How do I Prepare for a Data Scientist Interview?

How do I Prepare for a Data Scientist Interview?
source: 7wdata.be

So you have completed your data science course and are looking for a job. A career in data science is beyond completing your course and job-hunting. It is also a reflection of your passion for data and out-of-the-box thinking. So having good grades is not enough to ace the data science job interview. Your domain knowledge, portfolio, and technical skillsets also come into play and can swing any interview in your favor.

At the outset, register yourself for a data science course in Bangalore. Complete your lessons and work through your projects. Build a data science portfolio that stands out from the rest. The job market has plenty of mediocre and junior talent, and it is your portfolio and the way you present yourself at the interview that helps you land that much-coveted data scientist job.

Why be a data scientist?

At the outset, it helps to be clear about why you want to be a data scientist. It may even be a question you are asked at the interview.

You are passionate about data. You like to discover hidden trends and patterns and solve real-world problems. It offers a chance to gain business knowledge. And it presents you the opportunity to work with decision-makers and top executives in a job that pays handsomely!

How to prepare for a data science interview?

Data Scientist roles and responsibilities vary across industries and companies. Data scientist job roles also differ with varying job responsibilities. The skills required for different data scientist job positions differ. The format of the data scientist job interview also varies.

For success in the interview, you must be familiar with the format and understand what topics will be covered. Most interviews are now conducted over the phone or video call due to COVID, so familiarity with the interview app is necessary. Run through a quality check of all technicalities beforehand. For instance, if you are interviewed over a video conference you will need to share a screen with the interviewer to write and show your code. An in-person interview will have multiple data scientists on board with each interviewing on different topics.

Set yourself up for interview success by leveraging your strengths and interests and preparing well for the questions.

Walkthrough these steps to prepare for a data scientist interview.

Put together a solid resume and portfolio

Make sure your resume includes your GitHub account and the projects you have worked on, all of your qualifications and experiences, your knowledge of Python, SQL, predictive analytics, machine learning, and other tool kits. You may not have all the skills required of a data scientist, but you should tick at least half of them.

Know the company and its domain

Learn more about the company. Research about their domain, the work they do, their facilities, products, services, etc. Consider the kind of problems the interviewer might be asking. Technical questions may stem from the problems the company is working on. Knowing about the company and its activities will help you answer any related questions.

Domain knowledge and practical experience in the industry are much valued. So, learn about the industry domain and highlight any projects or work experience you have.

Take help from online platforms

Online platforms prepare you for data science interview questions, with mock interviews and project suggestions. Job sites also list previous interview questions with answers and tips. Look these up to support your interview prep curve.

Understand your job role

Data scientist job roles are many, and you must understand the job role you have applied for.  Some of the data science job roles are data analysts, data architects, business analysts, data scientists, machine learning engineers, data science architects, computer vision specialists, data engineers, AI engineers, data science generalists, and others.

Read through the job description to identify which data scientist profile the company is looking for. Research the role and the skills required in that role. Make sure your skill sets and interview preparation match the job role. Brush up your knowledge for data science role-specific questions.

For instance, if interviewing for a data science generalist job role you must keep in mind that it requires a deep understanding of mathematical and statistical concepts for designing and conducting research experiments and solving complex problems.

Prepare for the technical topics

Broadly, the main technical topics covered during the data scientist interview are:

  • Coding
  • Business Cases
  • Statistical Analysis and Probability
  • Modeling Techniques

Brush up on your ability to write complex SQL queries, prepare for simple data processing-oriented coding exercises using a script, and coding and logical (puzzle) questions.

Beginner-level questions may test your fundamental knowledge of statistics. Be ready with descriptive and inferential statistics. You are expected to be familiar with the mathematics and algorithms underlying machine learning.

Prepare for coding questions of data manipulation utilizing the code to uncover insights. Your coding skills, problem-solving abilities, and creativity are tested. Think of a typical software engineering interview.

Practice questions of statistical modeling and machine learning models, especially those related to the projects you have worked on.

Get ready for algorithm questions that demand the solution of a mathematical issue through code. These questions check your problem-solving and data manipulation skills in workplace situations.

Understand the experimental design and A/B testing, and how to interpret results statistically for interviews.

Practice mock interviews

Rehearse your pitch and answers to the key topics and your projects.

Be prepared for all topics. Practice solving problems, both verbally and written on paper.

Leverage your soft skills and display confidence. If you do not know the answer, do not lie and be accurate in whatever you say.

Takeaway

Most interviews begin with a question asking you to introduce yourself and move on to ask you about your project while testing your understanding of the basics. As a data scientist job role requires multiple skill sets and knowledge base, the interview questions include a mix-match of questions. Make sure that you tick all the boxes required by the hirer. Prepare for the interview and go ahead, nail it!

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