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NielsenIQ Data Scientist Interview Questions and Answers

Updated 22 Sep 2024

NielsenIQ Data Scientist Interview Experiences

5 interviews found

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

Related to basic statistics, and case study on sample design

Round 2 - Technical 

(2 Questions)

  • Q1. Explain the answers of case study on aptitude test
  • Q2. Sample design related questions
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Company Website and was interviewed in Jun 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

MCQS around aptitude and technical skills such as SQL, Python

Round 2 - Technical 

(1 Question)

  • Q1. Sql, Python, data science statistics

Interview Preparation Tips

Interview preparation tips for other job seekers - Study well and be prepared according to the JD

Data Scientist Interview Questions Asked at Other Companies

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Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Feb 2024. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Tell abt ur self
  • Ans. 

    I am a data scientist with a background in statistics and machine learning, passionate about solving complex problems using data-driven approaches.

    • I have a Master's degree in Data Science from XYZ University.

    • I have experience working with Python, R, and SQL for data analysis and modeling.

    • I have worked on projects involving predictive analytics, natural language processing, and computer vision.

    • I am proficient in data vi...

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

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

Round 1 - Technical 

(3 Questions)

  • Q1. Questions related to sampling
  • Q2. Questions related to outlier
  • Q3. Python basics questions
Round 2 - Aptitude Test 

Basic maths and statistics questions

NielsenIQ interview questions for designations

 Senior Data Analyst

 (3)

 Lead Data Analyst

 (1)

 Business Intelligence Analyst

 (1)

 Analytics Consultant

 (1)

 Data Analyst

 (7)

 Data Engineer

 (1)

 Data Processing Analyst

 (26)

 Data Processing Specialist

 (15)

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
More than 8 weeks
Result
Selected Selected

I was interviewed before Sep 2023.

Round 1 - Aptitude Test 

MCQ question stats & python based

Round 2 - Coding Test 

As selected in step 1

Round 3 - HR 

(1 Question)

  • Q1. Salary & relocation

Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. Please tell me something about yourself.What is your experience? What are your goals and ambitions?Why We should hire you? Strengths and weaknesses etc.

I applied via Recruitment Consultant and was interviewed in Dec 2018. There were 3 interview rounds.

Interview Questionnaire 

11 Questions

  • Q1. 1. Why Machine Learning?
  • Q2. 2. Why did you choose Data Science Field?
  • Ans. 

    I chose Data Science field because of its potential to solve complex problems and make a positive impact on society.

    • Fascination with data and its potential to drive insights

    • Desire to solve complex problems and make a positive impact on society

    • Opportunity to work with cutting-edge technology and tools

    • Ability to work in a variety of industries and domains

    • Examples: Predictive maintenance in manufacturing, fraud detection

  • Answered by AI
  • Q3. 3. What about Linear Regression? (Theory Part)
  • Q4. 4. What is the difference between Linear Regression and Logistic Regression?
  • Ans. 

    Linear Regression is used for predicting continuous numerical values, while Logistic Regression is used for predicting binary categorical values.

    • Linear Regression predicts a continuous output, while Logistic Regression predicts a binary output.

    • Linear Regression uses a linear equation to model the relationship between the independent and dependent variables, while Logistic Regression uses a logistic function.

    • Linear Regr...

  • Answered by AI
  • Q5. 5. Explain Confusion Matrix?
  • Ans. 

    Confusion matrix is a table used to evaluate the performance of a classification model.

    • It is a 2x2 matrix that shows the number of true positives, false positives, true negatives, and false negatives.

    • It helps in calculating various metrics like accuracy, precision, recall, and F1 score.

    • It is useful in identifying the strengths and weaknesses of a model and improving its performance.

    • Example: In a binary classification p...

  • Answered by AI
  • Q6. 6. Can we use confusion matrix in Linear Regression?
  • Ans. 

    No, confusion matrix is not used in Linear Regression.

    • Confusion matrix is used to evaluate classification models.

    • Linear Regression is a regression model, not a classification model.

    • Evaluation metrics for Linear Regression include R-squared, Mean Squared Error, etc.

  • Answered by AI
  • Q7. 7. Explain KNN Algorithm?
  • Ans. 

    KNN is a non-parametric algorithm used for classification and regression tasks.

    • KNN stands for K-Nearest Neighbors.

    • It works by finding the K closest data points to a given test point.

    • The class or value of the test point is then determined by the majority class or average value of the K neighbors.

    • KNN can be used for both classification and regression tasks.

    • It is a simple and easy-to-understand algorithm, but can be compu

  • Answered by AI
  • Q8. 8. Explain Random Forest and Decision Tree?
  • Ans. 

    Random Forest is an ensemble learning method that builds multiple decision trees and combines their outputs to improve accuracy.

    • Random Forest is a type of supervised learning algorithm used for classification and regression tasks.

    • It creates multiple decision trees and combines their outputs to make a final prediction.

    • Each decision tree is built using a random subset of features and data points to reduce overfitting.

    • Ran...

  • Answered by AI
  • Q9. 9. One Tricky Mathematical Question !
  • Q10. 10. What are the Projects you have done?
  • Ans. 

    I have worked on various projects involving data analysis, machine learning, and predictive modeling.

    • Developed a predictive model to forecast customer churn for a telecommunications company.

    • Built a recommendation system using collaborative filtering for an e-commerce platform.

    • Performed sentiment analysis on social media data to understand customer opinions and preferences.

    • Implemented a fraud detection system using anom...

  • Answered by AI
  • Q11. I didn't get shortlisted for 2nd Round.

Interview Preparation Tips

General Tips: anyone who wants to go in data science field should actually be interested in the field not the money. They should be good in Statistics, Probability and Theory part of ML algorithms.
They will ask you about the projects you have mentioned in resume and all the questions will be from that part.
Skills: Communication, Body Language, Problem Solving, Analytical Skills
Duration: 1-4 weeks

Skills evaluated in this interview

Data Scientist Interview Questions & Answers

C5i user image Kushal Kulkarni

posted on 18 Jun 2024

Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Not Selected

I was interviewed in May 2024.

Round 1 - Assignment 

Questions based on ML,PYTHON, DATA VISUALIZATION

Round 2 - Technical 

(2 Questions)

  • Q1. What is TF-IDF IN NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document

    • TF-IDF is calculated by multiplying the term frequency (TF) by the inverse document frequency (IDF)

    • It helps in identifying the most important

  • Answered by AI
  • Q2. Python coding questions based on list

Interview Preparation Tips

Interview preparation tips for other job seekers - Practice python
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Assignment 

ML,DL,Python,NLP,Data VIsualization

Round 2 - Technical 

(1 Question)

  • Q1. Explain TF-IDF in NLP
  • Ans. 

    TF-IDF is a numerical statistic that reflects the importance of a word in a document relative to a collection of documents.

    • TF-IDF stands for Term Frequency-Inverse Document Frequency.

    • It is used in Natural Language Processing (NLP) to determine the importance of a word in a document.

    • TF-IDF is calculated by multiplying the term frequency (TF) of a word by the inverse document frequency (IDF) of the word.

    • It helps in ident...

  • Answered by AI
Interview experience
5
Excellent
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed before Dec 2023. There were 3 interview rounds.

Round 1 - Coding Test 

Test of Basic data structures in Python include lists, tuples, and dictionaries, as well as loops and conditional statements.

Round 2 - Case Study 

Framework and requirements for chatbot implementation.

Round 3 - HR 

(1 Question)

  • Q1. Salary discussion
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NielsenIQ Interview FAQs

How many rounds are there in NielsenIQ Data Scientist interview?
NielsenIQ interview process usually has 2 rounds. The most common rounds in the NielsenIQ interview process are Technical, Aptitude Test and Coding Test.
How to prepare for NielsenIQ Data Scientist interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at NielsenIQ. The most common topics and skills that interviewers at NielsenIQ expect are Python, Data Science, Machine Learning, SQL and Cloud Computing.
What are the top questions asked in NielsenIQ Data Scientist interview?

Some of the top questions asked at the NielsenIQ Data Scientist interview -

  1. Tell abt ur s...read more
  2. Explain the answers of case study on aptitude t...read more
  3. Sql, Python, data science statist...read more

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NielsenIQ Data Scientist Interview Process

based on 5 interviews

1 Interview rounds

  • Aptitude Test Round
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NielsenIQ Data Scientist Salary
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₹4 L/yr - ₹14.2 L/yr
45% less than the average Data Scientist Salary in India
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