More articles in Interview Prep

Congratulations on being shortlisted for an interview! You are now one step closer to getting your dream job.

I’m sure you have the qualifications and skills required to get the job, but does that guarantee your selection? Getting your dream job is more than getting shortlisted for a job interview. Having the right skill set is one thing, but being able to demonstrate it in an interview is equally important. Soft skills such as communication skills, logical thinking, ability to work as part of a team, etc. will all be tested in an interview. So how can you prove to be the right candidate? Let us tell you how.

How to Prepare for a Job Interview

Before you begin preparing for your job interview, here are some generic articles to help you get started.

• How to Introduce Yourself in a Job Interview?
• How to Crack Data Science FAANG Jobs in 2024?

Now, preparing for a job interview is a 6-step process involving research and practice.

Research Phase

1. Know the role-based requirements
2. Understand the job description
3. Research about the company

Practice Phase

1. Practice on technical skills
2. Prepare answers to interview questions
3. Simulate the interview with mock interviews

Now let us go through each of the steps in detail.

Step 1: Know the Role-based Requirements

What you should do:

• Find out the educational qualifications and technical skills required for the job.
• Understand which of them are your strong suits and weak points.
• Prepare to build conversations and answers around your strong suits.
• Work on what you lack by doing online courses, or preparing with interview guides on those topics.

Main objectives:

• Gain a clear understanding of the skills required for the job role and where you stand.

Having the right skill set is one thing, but being able to efficiently communicate this with your interviewer is a skill on its own. Make sure you highlight your best skills and back them up with experience or previous projects. This will help in further letting the company know why you qualify for the position.

One of the best ways to show your technical skills in a Data Science or AI interview is by sharing your portfolio. Here are some resources that can guide you on how to make your portfolio stand out.

• How to Build a Portfolio for an AI Career
• How to make an impressive Data Science Portfolio
• Data Scientist Resume: Best Practices and Tips

If you’re thinking of what projects to add to your portfolio, here are some suggestions:

• 6 Open Source Data Science Projects That Provide an Edge to Your Portfolio
• 10 Data Science Projects Every Beginner Should Add to Their Portfolio

These projects will test your skills, help you brush up on your knowledge, and once done, show your interviewer what you are good at.

Step 2: Understand the Job Description

What you should do:

• Read through the job description thoroughly.
• Understand what a typical workday is like.
• Plan how to align your previous experiences with the given job description.
• Highlight related skills and similar responsibilities in your portfolio.

Main objectives:

• Get a clear idea of what tasks you will be doing on a typical workday.
• Know what teams you will be working with.
• Figure out how best to present your technical background.

Step 3: Research About the Company

What you should do:

• Check the company’s website and social media pages.
• Understand the goals and values of the company.
• Learn how the company operates and find out who you will be working with.
• Find prospective colleagues, HR, and the company’s ex-employees on LinkedIn or other similar platforms.
• Get in touch with them to know what the working conditions are like, what exactly your role will be, and some pros and cons of the job.

Main objectives:

• Gain a good understanding of the company to speak about it confidently in the interview.
• Know what questions to ask your interviewer regarding the company or your role.
• Understand your future working conditions.
• Make an informed decision about taking up the job

Step 4: Practice on Technical Skills

What you should do:

• Practice on the technical skills required for the job, especially if it is a hands-on coding role.
• Try learning new skills for the job by exploring some sample projects and solutions.

Main objective:

• Be prepared for any coding questions the interviewer may ask you.
• Build your portfolio with relevant projects that display your skillset.

Resources for Projects and Practice Problems

1. Top 18 Power BI Project Ideas For Practice 2024
2. Top 10 Platforms to Practice Data Science Skills
3. 7 Best Platforms to Practice Python
4. Top 10 Platforms to Practice SQL in 2024
5. Top 10 Tableau Projects for Data Science
6. 14 Exciting Mini Python Project Ideas for Beginners
7. Top 10 Web Scraping Projects to Do in 2024
8. 5 Free Data Science Projects With Solutions
9. 20 Data Engineering Project Ideas with Source Code
10. Top 10 Generative AI Projects
11. Top 14 Data Mining Projects With Source Code
12. 10 Exciting Projects on Large Language Models (LLM)
13. Top 10 SQL Projects for Data Analysis
14. Top 10 Data Analytics Projects with Source Codes
15. Learn and Test your Machine Learning Skills with AV’s New Practice Problems and Free Courses!

So practice on some sample projects beforehand and brush up your technical skills while prepping for your interview.

Step 5: Prepare Answers to Interview Questions

What you should do:

• Go through interview question guides on all the topics related to.
• Emphasize more on the topics shortlisted in step 2.
• If preparing to give a written test, practice answering the MCQs on related topics.

Main objectives:

• Be prepared for any technical or non-technical questions you maybe asked at your interview.
• Gain a thorough understanding of all topics related to the job role.

Interview Question Guides on Specific Technical Skills

1. SQL (Query Language): Top 10 SQL Interview Questions With Implementation
2. Shell Scripting (Scripting Language/Skill): 30+ Shell Scripting Interview Questions
3. DBMS (Database Management Systems – General Concept): Top 40 DBMS Interview Questions and Answers
4. Data Modelling (Data Science Concept): Data Modeling Interview Questions
5. NoSQL (Database Concept): Interview Questions on NoSQL
6. Probability (Mathematical Concept): 25 Probability and Statistics Questions to Ace Your Data Science Interviews
7. Statistics (Mathematical Discipline): Top 40 Data Science Statistics Interview Questions
8. Linear Regression (Statistical/Machine Learning Algorithm): 25 Questions to Test Your Skills on Linear Regression Algorithm
9. Reinforcement Learning (Machine Learning Technique): Top 5 Interview Questions on Reinforcement Learning
10. SVM (Support Vector Machine – Machine Learning Algorithm): Interview Questions on Support Vector Machines
11. Python (Programming Language): 90+ Python Interview Questions and Answers (2024 Edition)
12. RAG (Retrieval-Augmented Generation): Top 20+ RAG Interview Questions

Interview Question Guides on Database Management Software

1. MySQL (Database Management System): Top 30+ MySQL Interview Questions
2. MongoDB (NoSQL Database): 50+ MongoDB Interview Questions and Answers
3. Cassandra (NoSQL Database): Top 6 Cassandra Interview Questions
4. Microsoft HDFS (Hadoop Distributed File System): Top 6 Microsoft HDFS Interview Questions
5. Hadoop (Framework for Distributed Storage and Processing): Top 10 Hadoop Interview Questions You Must Know
6. Apache Oozie (Workflow Scheduler for Hadoop): Top 5 Interview Questions on Apache Oozie

Interview Question Guides on Data Science Tools

1. AWS (Cloud Service Platform): Top 30 AWS Interview Questions with Answers
2. Tableau (Data Visualization Software): Top 40 Tableau Interview Questions and Answers for 2024
3. Excel (Spreadsheet Software): 50+ Excel Interview Questions to Ace Your Interview
4. Snowflake (Cloud Data Warehousing Software): 15+ Snowflake Interview Questions and Answers
5. GCP (Google Cloud Platform): 34 Must-Know GCP Interview Questions for 2024
6. Azure Data Factory (Cloud-based Data Integration Service): 20 Most Frequently Asked Azure Data Factory Interview Questions
7. GCP BigQuery (Cloud Data Warehouse): Top Google BigQuery Frequently Asked Interview Questions
8. Amazon S3 (Cloud Storage Service): Top 6 Amazon S3 Interview Questions
9. Amazon Redshift (Cloud Data Warehousing Service): Top 6 Amazon Redshift Interview Questions
10. AWS DynamoDB (NoSQL Database Service): Top 30 AWS Interview Questions with Answers
11. PowerBi: Power BI Interview Questions & Answers 2024

Interview Question & Answer Video Guides

1. Top 21 Python Interview Questions & Answers
2. Python Coding Interview Questions & Answers – Part 1
3. Python Coding Interview Questions & Answers – Part 2 
4. Top Interview Questions for Artificial Intelligence, Generative AI and LLMs to Land AI Jobs in 2024
5. Statistics Interview Questions and Answers for Data Science
6. Top 10 Deep Learning Interview Questions And Answers – Part 1
7. Top 10 Deep Learning Interview Questions and Answers – Part2
8. Artificial Intelligence Interview Questions and Answers
9. Data Analytics Interview Questions and Answers
10. SQL Interview Questions and Answers

Resources to Prepare for an AI Job Interview

• How to Prepare for an AI Job Interview?
• Top 50 AI Interview Questions with Answers
• 60+ Generative AI Terms You Must Know By Heart
• 5 Strategies for Acing Your AI Technical Interview

Resources to Prepare for an Data Science Job Interview

1. Top 15 Data Structures Interview Questions
2. Top 50 Google Interview Questions for Data Science Roles
3. Tips and Tricks to Crack Campus Placement in Data Science
4. 10 Important Questions for Cracking a Data Science Interview
5. 40 Data Science Coding Questions and Answers for 2024
6. Top 30 Deep Learning Interview Questions for Data Scientists
7. Top 30+ Big Data Interview Questions
8. Most Essential 2024 Interview Questions on Data Engineering
9. Top 50 Data Warehouse Interview Questions and Answers
10. Top 100 Data Science Interview Questions & Answers 2024

Resources to Prepare for a Machine Learning Job Interview

1. 40 ML Interview Questions That You Must Know [2024]
2. 30+ LLM Interview Questions and Answers
3. Top 9 Fine-tuning Interview Questions and Answers
4. Important Keras Questions for Cracking Deep Learning Interviews
5. 25 Questions to Test Your Skills on ANN
6. Top 25 Interview Questions on RNN
7. Interview Questions on KNN in Machine Learning
8. Top 40 Machine Learning Questions & Answers for Beginners and Experts (Updated 2024)
9. 15 Mlops Interview Questions for 2024
10. Interview Questions on Bagging Algorithms in Machine Learning

Step 6: Simulate the Interview with Mock Interviews

What you should do:

• Find a mentor to guide you through the interview process. This could be a professor, industry leader, or someone who is currently in the same job role.
• Once prepared, ask them to give you a mock trial of how the interview is going to be.
• Take a mock interview, see how you fare, and work on your weak points till you master it.

Main objective:

• Be completely prepared for your AI or Data Science job interview.

How you talk and present ideas in the interview is sometimes even more important than being qualified for the job. So taking a mock interview will give you a feel of the real deal. Alternatively, you can use AI tools such as Liftoff AI to practice your interview skills.

If you are having a telephonic interview, here are some tips that will help you ace it.

Once you have followed all these steps, I’m sure you will be ready to impress your interviewers. You will be well prepared for any theoritical, technical, and non-technical questions thrown at you. Your portfolio will shine over your competitors and you will surely get the job you deserve. So go ahead, and get that dream job!