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Myntra Business Analyst Interview Questions – Day 3

Myntra Business Analyst Interview Questions

Company Name – Myntra
Designation – Business Analyst
Salary – 15 to 18 LPA (Depending on current CTC and graduation college)
Number of rounds – 4
Level of questions – Moderate to Hard

Myntra Business Analyst Interview Questions

Myntra Business Analyst Interview Questions
Myntra Business Analyst Interview Questions

Round 1 – 50 MCQs to be solved in 60 minutes
Round 2 – Technical Round with focus on SQL and Python (Pandas and Numpy)
Round 3 – Case Study Round
Round 4 – Hiring Manager with some SQL coding

Round 1 – MCQs

There were 50 questions that was supposed to be solved in one hour. There were 40 MCQs and 10 query writing questions. We can’t disclose the exact questions as it is still used for recruitment but below is the type of questions asked:-
1. Calculating date difference between two dates
2. Extracting string using Regular expression
3. Output of outer join
4. Caluclating cumulative sum on a data set
5. Difference between rank() and dense_rank()
6. Finding error in query (mostly on group by and aggregate functions)
7. Difference between key (primary and foreign key)
8. Output of simple but confusing commands like Select ‘1’+2 or Select Null+’2′

Round 2 – SQL and Python

Following is the link to the questions, most of the questions are solved by the fellow Analytics professionals. Do check it out

Find all the students who either are male or live in Mumbai ( have Mumbai as a part of their address).
Get all the distinct email id from a column in SQL
Join two tables without using any common column
Output based question
Output based question – 2

Python Questions

1. Difference between mutable and immutable data type
2. Missing data treatment using Pandas
3. Join and group by syntax
4. Write a nested lambda function to multiply two numbers.
5. Difference between parameter and argument

Round 3 – Case Study

There were a variety of case studies asked to different candidates, the one asked to me was

Can you choose a strategy for increasing the number of songs listened by the user on an online application? How will you decide the types of playlists to suggest him?


Mainly I will tackle this problem like any recommendation engine.

Machine learning algorithms in recommender systems are typically classified under two main categories :

1.  Content-based – strategy relies on analyzing factors and demographics that are directly associated with the user or product, such as the age, sex and demographic of the user or a song genre or playlist,

2. Collaborative filtering – Collaborative Filtering takes consumer behavior data and utilizes it to predict future behavior This consumer behavior leaves a trail of data, generated through implicit and explicit feedback, based on the user’s listening history, in tandem with songs enjoyed by users who seem to have a similar history

Round 4 – Hiring Manager Round

Hiring Manager round was mostly around work experience and past projects, but be prepared to have a few questions on SQL (related to your project) and a few basic questions on statistics.

First round is the most important as your score is passed to all the following rounds. A few questions might be asked from the 1st round question(that you might have messed up)

The Data Monk Interview Books – Don’t Miss

Now we are also available on our website where you can directly download the PDF of the topic you are interested in. On Amazon, each book costs ~299, on our website we have put it at a 60-80% discount. There are ~4000 solved interview questions prepared for you.

10 e-book bundle with 1400 interview questions spread across SQL, Python, Statistics, Case Studies, and Machine Learning Algorithms – Ideal for 0-3 years experienced candidates

23 E-book with ~2000 interview questions spread across AWS, SQL, Python, 10+ ML algorithms, MS Excel, and Case Studies – Complete Package for someone between 0 to 8 years of experience (The above 10 e-book bundle has a completely different set of e-books)

12 E-books for 12 Machine Learning algorithms with 1000+ interview questions – For those candidates who want to include any Machine Learning Algorithm in their resume and to learn/revise the important concepts. These 12 e-books are a part of the 23 e-book package

Individual 50+ e-books on separate topics

Important Resources to crack interviews (Mostly Free)

There are a few things that might be very useful for your preparation

The Data Monk Youtube channel – Here you will get only those videos that are asked in interviews with Data Analysts, Data Scientists, Machine Learning Engineers, Business Intelligence Engineers, Analytics managers, etc.
Go through the watchlist which makes you uncomfortable:-

All the list of 200 videos
Complete Python Playlist for Data Science
Company-wise Data Science Interview Questions – Must Watch
All important Machine Learning Algorithm with code in Python
Complete Python Numpy Playlist
Complete Python Pandas Playlist
SQL Complete Playlist
Case Study and Guesstimates Complete Playlist
Complete Playlist of Statistics

Keep Learning !!


About TheDataMonkGrand Master

I am the Co-Founder of The Data Monk. I have a total of 6+ years of analytics experience 3+ years at Mu Sigma 2 years at OYO 1 year and counting at The Data Monk I am an active trader and a logically sarcastic idiot :)

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