Tiger Analytics Interview Experience for Sr. Data Analyst

Recently, I have been through the interview experience of Tiger Analytics and would like to share my whole interview experience. Each round was an elimination round for the interview process.

In total there are 4 rounds:

1. Resume Shortlist
2. Aptitude & Coding Test round
3. Technical Round
4. Final Technical Round

There are two ways you can apply for an interview:  via LinkedIn or University Campus Round.

Interview Process:

Resume Shortlisting: I customize my resume into 4 different parts. 

• Firstly I included all the details such as LinkedIn, email, Tableau/PowerBI projects, and Website.
• Second, I included all my internship experiences with the certificates and add bullet points in which I helped the company with various projects. 
• Third I added a different section for skills, soft skills showing my skills.
• Fourth I added all the certificates and my projects with the links for displaying the project.

Aptitude & Coding Test round: This round is the most crucial as it will be degerming your chance of getting into further rounds. This round consists of 20 MCQs having aptitude questions and some technical questions.

The syllabus of the aptitude test

• A highly important topic is probability most of the questions will have a probability topic in them.
• Permutation and Combination
• Height and Distance, Work and Time
• In geometry the questions are easy don’t have to practice thoroughly just looking at some formulas once will help a lot.
  

Live coding round: Each person will get a test link where the HackerEarth link will be there. There were numerous questions each question carries different marks ranging from 10 to 100. The most common questions are based on DP and Segment Tree.

Previous Project Discussion  + Technical Round: The interviewer told me to introduce myself and talk about what kind of projects I have done previously. 

After that, the questions round will start where the topics can be of 

• Problem-solving, 
• Basic theories of Machine Learning.
• They will be asking about some advanced question based on NLP or Computer vision based on your projects and work experience.
• Some questions based on use cases where the scenario will be there and you have to give a solution, based on your solution they will cross question you. 
• Some question will be related to Advanced SQL based on the scenario they give.
• Some question based on any visualization tool you used PowerBI / Tableau / Plotly 

Question based on Machine Learning

• What is bias-variance 
• When to use which type of Metrics 
• Some statics and probability question too
• Some question related to AB testing
• Without using feature engineering how to increase the efficiency of the model

They will ask some question about parameters used in the ML algorithm

Tips for learning and improving

• Always make sure to add your best projects which actually serves a purpose and meaning not just some Kaggle projects where a interview can find 1000 of notebook already.
• Don’t just add a simple jupyter notebook make a simple live demo and explained how it worked and what was your motive to make. lastly, don’t forgot to say what is your current interest domain that you would like to work on.
• Always have a simple and answer the question likewise. If you don’t know the answer don’t play around the bush and say I don’t have enough expertise in that area.