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Nielsen Data Scientist Interview Questions, Process, and Tips

Updated 7 Jan 2025

Top Nielsen Data Scientist Interview Questions and Answers

  • Q1. Write pandas query to separate the names as first and last name from the full name. Drop the duplicate columns and also the missing values. Write output for the Python co ...read more
  • Q2. Make 2 lists a=[1,2,3,4] b=[9,8,5,5,2,3,3,4,1,1,10,9,2,3,4,10,10,9,7,7,8] Write a program to remove duplicate of b and keep only those elements of b which are not present ...read more
  • Q3. SQL question Remove duplicate from a table tab1

Nielsen Data Scientist Interview Experiences

4 interviews found

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
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in May 2024. There were 3 interview rounds.

Round 1 - Coding Test 

I was asked to write SQL queries for 3rd highest salary of the employee, some name filtering, group by tasks.
Python code to find the index of the maximum number without using numpy.

Round 2 - One-on-one 

(1 Question)

  • Q1. Explain the Project undertaken during the research and follow-up questions
Round 3 - Technical 

(1 Question)

  • Q1. Write pandas query to separate the names as first and last name from the full name. Drop the duplicate columns and also the missing values. Write output for the Python code. Write SQL query to retrieve t...
  • Ans. 

    Answering questions related to data science concepts and techniques.

    • Recall is the ratio of correctly predicted positive observations to the total actual positives. Precision is the ratio of correctly predicted positive observations to the total predicted positives.

    • To reduce variance in an ensemble model, techniques like bagging, boosting, and stacking can be used. Bagging involves training multiple models on different ...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Nielsen Data Scientist interview:
  • Python
  • Pandas
  • SQL
  • Machine Learning
Interview preparation tips for other job seekers - Have your basics strong.

Skills evaluated in this interview

Data Scientist Interview Questions Asked at Other Companies

Q1. for a data with 1000 samples and 700 dimensions, how would you fi ... read more
Q2. Special Sum of Array Problem Statement Given an array 'arr' conta ... read more
asked in Affine
Q3. you have a pandas dataframe with three columns, filled with state ... read more
Q4. Clone a Linked List with Random Pointers Given a linked list wher ... read more
asked in Coforge
Q5. coding question of finding index of 2 nos. having total equal to ... read more
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed in Oct 2023. There were 4 interview rounds.

Round 1 - Coding Test 

Sql, python, Statistics mcq, Aptitude test. These were medium level questions.

Round 2 - Technical 

(3 Questions)

  • Q1. SQL and python, time complexity
  • Q2. Make 2 lists a=[1,2,3,4] b=[9,8,5,5,2,3,3,4,1,1,10,9,2,3,4,10,10,9,7,7,8] Write a program to remove duplicate of b and keep only those elements of b which are not present in a, and the final list should ...
  • Ans. 

    Remove duplicates from list b, keep elements not in list a, and sort in ascending order.

    • Create a set from list b to remove duplicates

    • Use list comprehension to keep elements not in list a

    • Sort the final list in ascending order

  • Answered by AI
  • Q3. SQL question Remove duplicate from a table tab1
  • Ans. 

    Use the DISTINCT keyword in SQL to remove duplicates from a table.

    • Use the SELECT DISTINCT statement to retrieve unique rows from the table.

    • Identify the columns that should be used to determine uniqueness.

    • Example: SELECT DISTINCT column1, column2 FROM tab1;

  • Answered by AI
Round 3 - Case Study 

Given 2 case studies on data science and asked different possibilities to improve the models.

How to work with imbalance dataset.
How to remove null values, what is features engineering.
What is PCA
What is the working of XGBOOST

Round 4 - Project discussion 

(1 Question)

  • Q1. What was last project, tell me in detail. There were different technical questions related to my project

Interview Preparation Tips

Interview preparation tips for other job seekers - Be confident and practice SQL, python, mainly pandas and numpy. Should have good knowledge on time complexity.


All the metrics of evaluating a model.
Linear regression, logestic regression, random forest, decission tree, adaboost, Gradient boosting, XGb in detail.

Recall, precision roc_curve. Auc, f1 score, mse,mae, r2, adjusted r2 score.

Is it possible that r2 score appears in minus

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Mar 2024. There were 4 interview rounds.

Round 1 - Aptitude Test 

Test consisted 7 sections which lasted for more than a hour. There were questions related to coding , sql , analytical questions etc.

Round 2 - Coding Test 

1 python coding questions and 2 Sql question

Round 3 - Case Study 

2 case study question

Round 4 - HR 

(1 Question)

  • Q1. This was the final round . Technical+HR .

Interview Preparation Tips

Interview preparation tips for other job seekers - All the best. Interview process is too long , have patience. And be prepared , questions will be basic.

Nielsen interview questions for designations

 Senior Data Scientist

 (2)

 Executive Data Scientist

 (1)

 Data Engineer

 (5)

 Data Analyst

 (3)

 Senior Data Engineer

 (2)

 Data Processing Executive

 (1)

 Data Processing Specialist

 (1)

 Lead Data Engineer

 (1)

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Jan 2025.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Can you elaborate on your work experience?
  • Ans. 

    I have 5 years of experience in analyzing large datasets to extract valuable insights and make data-driven decisions.

    • Analyzed customer behavior data to optimize marketing strategies

    • Built predictive models to forecast sales trends

    • Utilized machine learning algorithms to improve product recommendations

    • Presented findings to stakeholders in a clear and actionable manner

  • Answered by AI
  • Q2. What questions were asked regarding your work experience?
  • Ans. 

    Questions related to work experience in data science field.

    • Asked about previous projects worked on

    • Inquired about specific data analysis techniques used

    • Discussed challenges faced and how they were overcome

  • Answered by AI
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
No response

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

Round 1 - Technical 

(2 Questions)

  • Q1. Cross validation
  • Q2. How to handle imbalanced dataset
  • Ans. 

    Handling imbalanced datasets involves techniques like resampling, using different algorithms, and adjusting class weights.

    • Use resampling techniques like oversampling the minority class or undersampling the majority class.

    • Utilize algorithms that are robust to imbalanced datasets, such as Random Forest, XGBoost, or SVM.

    • Adjust class weights in the model to give more importance to the minority class.

    • Use techniques like SMO...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - most questions will be from your projects/work exp

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected
Round 1 - Aptitude Test 

Basic aptitude question from rs aggarwal book.

Round 2 - Coding Test 

Basic questions on python loops

Round 3 - Group Discussion 

Try to put foeth yiur point as there will 13 people in a panel

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

Given 6 coding qns related to java and html and also ML.

Round 2 - Technical 

(1 Question)

  • Q1. Explain abt projects and qns related to ML.
  • Ans. 

    Projects in machine learning involve developing algorithms to analyze and interpret data for various applications.

    • Developing a recommendation system for an e-commerce website

    • Predicting customer churn for a telecommunications company

    • Classifying images in a computer vision project

    • Anomaly detection in network traffic for cybersecurity

    • Natural language processing for sentiment analysis

  • Answered by AI
Round 3 - HR 

(1 Question)

  • Q1. Basic hr qns why straive?

Skills evaluated in this interview

Nielsen Interview FAQs

How many rounds are there in Nielsen Data Scientist interview?
Nielsen interview process usually has 3 rounds. The most common rounds in the Nielsen interview process are Coding Test, Technical and Case Study.
How to prepare for Nielsen 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 Nielsen. The most common topics and skills that interviewers at Nielsen expect are Django, Docker, Numpy, Pandas and Pyspark.
What are the top questions asked in Nielsen Data Scientist interview?

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

  1. Write pandas query to separate the names as first and last name from the full n...read more
  2. Make 2 lists a=[1,2,3,4] b=[9,8,5,5,2,3,3,4,1,1,10,9,2,3,4,10,10,9,7,7,8] Wri...read more
  3. SQL question Remove duplicate from a table t...read more

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Nielsen Data Scientist Interview Process

based on 4 interviews

Interview experience

4
  
Good
View more
Nielsen Data Scientist Salary
based on 40 salaries
₹6 L/yr - ₹18.5 L/yr
21% less than the average Data Scientist Salary in India
View more details

Nielsen Data Scientist Reviews and Ratings

based on 8 reviews

4.6/5

Rating in categories

3.8

Skill development

4.6

Work-life balance

4.0

Salary

4.5

Job security

4.5

Company culture

4.0

Promotions

4.1

Work satisfaction

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