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NielsenIQ Data Scientist Interview Questions and Answers
NielsenIQ Data Scientist Interview Experiences
5 interviews found
Anonymous
I applied via Company Website and was interviewed in Jun 2024. There were 2 interview rounds.
MCQS around aptitude and technical skills such as SQL, Python
(1 Question)
- Q1. Sql, Python, data science statistics
Interview Preparation Tips
Related to basic statistics, and case study on sample design
(2 Questions)
- Q1. Explain the answers of case study on aptitude test
- Q2. Sample design related questions
Ammu Nandy
Selected
I applied via Referral and was interviewed in Feb 2024. There was 1 interview round.
(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...
Selected
I applied via Referral and was interviewed before Jun 2023. There were 2 interview rounds.
(3 Questions)
- Q1. Questions related to sampling
- Q2. Questions related to outlier
- Q3. Python basics questions
Basic maths and statistics questions
NielsenIQ interview questions for designations
Selected
I was interviewed before Sep 2023.
MCQ question stats & python based
As selected in step 1
(1 Question)
- Q1. Salary & relocation
Interview questions from similar companies
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
(6 Questions)
- Q1. Which GenAI projects I have worked on
- Q2. What is the context window in LLMs
- Ans.
Context window in LLMs refers to the number of surrounding words considered when predicting the next word in a sequence.
Context window helps LLMs capture dependencies between words in a sentence.
A larger context window allows the model to consider more context but may lead to increased computational complexity.
For example, in a context window of 2, the model considers 2 words before and 2 words after the target word fo
- Q3. What is top_k parameter
- Ans.
top_k parameter is used to specify the number of top elements to be returned in a result set.
top_k parameter is commonly used in machine learning algorithms to limit the number of predictions or recommendations.
For example, in recommendation systems, setting top_k=5 will return the top 5 recommended items for a user.
In natural language processing tasks, top_k can be used to limit the number of possible next words in a
- Q4. What are regex patterns in python
- Ans.
Regex patterns in Python are sequences of characters that define a search pattern.
Regex patterns are used for pattern matching and searching in strings.
They are created using the 're' module in Python.
Examples of regex patterns include searching for email addresses, phone numbers, or specific words in a text.
- Q5. What are iterators and tuples
- Ans.
Iterators are objects that allow iteration over a sequence of elements. Tuples are immutable sequences of elements.
Iterators are used to loop through elements in a collection, like lists or dictionaries
Tuples are similar to lists but are immutable, meaning their elements cannot be changed
Example of iterator: for item in list: print(item)
Example of tuple: my_tuple = (1, 2, 3)
- Q6. Do I have REST API experience
- Ans.
Yes, I have experience working with REST APIs in various projects.
Developed RESTful APIs using Python Flask framework
Consumed REST APIs in data analysis projects using requests library
Used Postman for testing and debugging REST APIs
Skills evaluated in this interview
Satya sai
I was interviewed in Aug 2024.
(2 Questions)
- Q1. DFA Focus :Sorting ,Searching ,Stacks,Queues, HashMaps
- Q2. Os & cn: Process scheduling, TCP/IP, HTTP basics
I was interviewed in May 2024.
(2 Questions)
- Q1. Tell me about your self?
- Q2. What is maths and stats
- Ans.
Maths and stats refer to the study of mathematical concepts and statistical methods for analyzing data.
Maths involves the study of numbers, quantities, shapes, and patterns.
Stats involves collecting, analyzing, interpreting, and presenting data.
Maths is used to solve equations, calculate probabilities, and model real-world phenomena.
Stats is used to make informed decisions, draw conclusions, and test hypotheses.
Both ma...
Confusion matrix what are your job rolls explain me Gradient boosting algorithm?
Interview Preparation Tips
(2 Questions)
- Q1. Number of Duplicate words in a string
- Ans.
Count the number of duplicate words in a string.
Split the string into words using a delimiter like space or punctuation.
Create a dictionary to store the count of each word.
Iterate through the words and increment the count in the dictionary.
Count the number of words with count greater than 1 as duplicates.
- Q2. Chunking in LLM
- Ans.
Chunking in LLM refers to breaking down text into smaller chunks for better processing by the language model.
Chunking helps improve the efficiency of the language model by breaking down large text inputs into smaller segments.
It can help the model better understand the context and relationships within the text.
Chunking is commonly used in natural language processing tasks such as text summarization and sentiment analys
Skills evaluated in this interview
Selected
I applied via Referral and was interviewed in Sep 2023. There were 5 interview rounds.
General maths n reasoning ques
1 DSA medium level question were asked
Any random topic that we have to speak upon
(2 Questions)
- Q1. Discussed everything written in the resume
- Q2. Skillsets written in resume
Interview Preparation Tips
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NielsenIQ Interviews By Designations
- NielsenIQ Data Processing Analyst Interview Questions
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Interview Questions for Popular Designations
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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 Reviews and Ratings
based on 10 reviews
Rating in categories
|
Data Processing Analyst
782
salaries
|  ₹3 L/yr - ₹4.8 L/yr |
|
Data Analyst
455
salaries
| ₹2.8 L/yr - ₹5.5 L/yr |
|
Data Processing Specialist
332
salaries
| ₹3 L/yr - ₹4.7 L/yr |
|
Software Engineer
239
salaries
| ₹8 L/yr - ₹21 L/yr |
|
Research Associate
175
salaries
| ₹2.9 L/yr - ₹5 L/yr |
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