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Mu Sigma Jr. Data Scientist Interview Questions and Answers

Updated 15 Jun 2022

Mu Sigma Jr. Data Scientist Interview Experiences

1 interview found

I applied via campus placement at New Horizon College of Engineering, Bangalore and was interviewed in May 2022. There were 3 interview rounds.

Round 1 - Aptitude Test 

The apptitude was quiet simple and straight forward.

Round 2 - Group Discussion 

GD topics were very simple and easy.they just expected us to make points that were creative and different

Round 3 - One-on-one 

(2 Questions)

  • Q1. Tell me something that you learnt technically Tell me something in which you failed about 20 to 30 Times
  • Q2. Describe the project you worked on

Interview Preparation Tips

Topics to prepare for Mu Sigma Jr. Data Scientist interview:
  • Data Science
Interview preparation tips for other job seekers - Be confident and bold just give them a assurance that you can learn the process.

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
-
Result
Selected Selected

I applied via Campus Placement and was interviewed before Mar 2023. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Puzzles, problem solving statement (available in gfg)
Round 2 - Technical 

(2 Questions)

  • Q1. Questions from project mentioned in resume
  • Q2. SQL, algorithms basic questions (algos used in the project)
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Referral and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Technical 

(5 Questions)

  • Q1. How will you find loyal customers for a store like DMart , SmartBazar
  • Ans. 

    Utilize customer transaction data and behavior analysis to identify loyal customers for DMart and SmartBazar.

    • Use customer transaction history to identify frequent shoppers

    • Analyze customer behavior patterns such as repeat purchases and average spend

    • Implement loyalty programs to incentivize repeat purchases

    • Utilize customer feedback and reviews to gauge loyalty

    • Segment customers based on their shopping habits and preferenc

  • Answered by AI
  • Q2. Who is more valuable a customer who is making small transactions everyday or the customer who makes big transactions in a month
  • Ans. 

    It depends on the business model and goals of the company.

    • Small transactions everyday can lead to consistent revenue streams and customer engagement.

    • Big transactions in a month can indicate high purchasing power and potential for larger profits.

    • Consider customer lifetime value, retention rates, and overall business strategy when determining value.

  • Answered by AI
  • Q3. What will you do as a data scientist if the sales of a store is declining
  • Ans. 

    I would conduct a thorough analysis of the sales data to identify trends and potential causes of the decline.

    • Review historical sales data to identify patterns or seasonality

    • Conduct customer surveys or interviews to gather feedback

    • Analyze competitor data to understand market dynamics

    • Implement predictive modeling to forecast future sales

    • Collaborate with marketing team to develop targeted strategies

  • Answered by AI
  • Q4. We have to bundle the items together in the units of 2-3 as a single units like chips of 3 packets together. how to identify which items to bundle and number of units. Create a machine learning model for i...
  • Q5. You are working in a project, where your approach towards problem is more innovative while the rest of the team is following conventional approach. how will you convince them to follow your approach.
  • Ans. 

    I would showcase the potential benefits and results of my innovative approach to convince the team.

    • Highlight the advantages of the innovative approach such as improved efficiency, accuracy, or cost-effectiveness.

    • Provide real-world examples or case studies where similar innovative approaches have led to successful outcomes.

    • Encourage open discussion and collaboration within the team to explore the potential of combining ...

  • Answered by AI
Round 2 - Case Study 

1. A store has promotional offers how will you analyse that offers are working in their favour.
2. What data will you require if you want to predict the sales of the chocolate in a store.
3. Why data is distributed normally in linear regression.
4. Difference between linear and logistic regression
5. A person who is senior to you and you are working on the same project. But that person has very bad reputation of misbehaving and being rude to people. And he is doing same with you. What will you do?

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare case study a lot. Both round were mainly revolving around case study and situational HR questions. Coding questions were not asked a lot. only few that too were quite easy.

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Naukri.com and was interviewed in Dec 2024. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Explain any ML model.
  • Q2. Create Dataframe from two lists.

Interview Preparation Tips

Topics to prepare for Nielsen Data Scientist interview:
  • Python
  • pandas
  • ML
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
-

I applied via Company Website and was interviewed in Aug 2024. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Explain the RAG pipeline?
  • Ans. 

    RAG pipeline is a data processing pipeline used in data science to categorize data into Red, Amber, and Green based on certain criteria.

    • RAG stands for Red, Amber, Green which are used to categorize data based on certain criteria

    • Red category typically represents data that needs immediate attention or action

    • Amber category represents data that requires monitoring or further investigation

    • Green category represents data that...

  • Answered by AI
  • Q2. Explain Confusion metrics
  • Ans. 

    Confusion metrics are used to evaluate the performance of a classification model by comparing predicted values with actual values.

    • Confusion matrix is a table that describes the performance of a classification model.

    • It consists of four different metrics: True Positive, True Negative, False Positive, and False Negative.

    • These metrics are used to calculate other evaluation metrics like accuracy, precision, recall, and F1 s...

  • Answered by AI

Skills evaluated in this interview

Interview experience
1
Bad
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

DSA and ML, AI, Coding question

Round 2 - One-on-one 

(1 Question)

  • Q1. Case study which was easy
Round 3 - One-on-one 

(1 Question)

  • Q1. In depth questions on ML
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed in Apr 2024. There were 2 interview rounds.

Round 1 - Case Study 

Excel data analytics case

Round 2 - Technical 

(1 Question)

  • Q1. Data analytics, data visualisation tools

Interview Preparation Tips

Interview preparation tips for other job seekers - Learn Clik and SQL
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed in Apr 2024. There was 1 interview round.

Round 1 - Coding Test 

SQL, Python coding …

Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-

I applied via campus placement at National Institute of Technology (NIT), Warangal

Round 1 - Aptitude Test 

1 hour aptitude test

Round 2 - One-on-one 

(1 Question)

  • Q1. What is one hot encoding
Round 3 - HR 

(1 Question)

  • Q1. What is your long term goal
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed before May 2023. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Sql, Python programming Questions
Round 2 - Technical 

(1 Question)

  • Q1. Retail, CPG based case study questions like offer allocation method for loyal customers

Mu Sigma Interview FAQs

How many rounds are there in Mu Sigma Jr. Data Scientist interview?
Mu Sigma interview process usually has 3 rounds. The most common rounds in the Mu Sigma interview process are Aptitude Test, Group Discussion and One-on-one Round.

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₹6.5 L/yr - ₹10 L/yr
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