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C5i Data Scientist Interview Questions, Process, and Tips

Updated 17 Dec 2024

Top C5i Data Scientist Interview Questions and Answers

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C5i Data Scientist Interview Experiences

4 interviews found

Data Scientist Interview Questions & Answers

user image rustam garg

posted on 4 May 2019

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?
  • Ans. 

    Machine learning enables computers to learn from data and make predictions or decisions without being explicitly programmed.

    • Machine learning can automate and optimize complex processes

    • It can help identify patterns and insights in large datasets

    • It can improve accuracy and efficiency in decision-making

    • Examples include image recognition, natural language processing, and predictive analytics

    • It can also be used for anomaly

  • Answered by AI
  • 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

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

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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

C5i interview questions for designations

 Data Analyst

 (2)

 Junior Data Analyst

 (2)

 Junior Business Analyst

 (1)

Data Scientist Jobs at C5i

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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
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
4
Good
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
Selected Selected

I applied via campus placement at Sastra University and was interviewed in Sep 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Along with coding round..there's a communication test at the end

Round 2 - Technical 

(2 Questions)

  • Q1. There's ntg to ask about technical for me..
  • Q2. Behavioural questions
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
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

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

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

Round 1 - One-on-one 

(2 Questions)

  • Q1. Scenario based questions
  • Q2. Video synthesis

C5i Interview FAQs

How many rounds are there in C5i Data Scientist interview?
C5i interview process usually has 2-3 rounds. The most common rounds in the C5i interview process are Assignment, Technical and Coding Test.
How to prepare for C5i 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 C5i. The most common topics and skills that interviewers at C5i expect are Python, Data Science, Machine Learning, SQL and Deep Learning.
What are the top questions asked in C5i Data Scientist interview?

Some of the top questions asked at the C5i Data Scientist interview -

  1. 4. What is the difference between Linear Regression and Logistic Regressi...read more
  2. 2. Why did you choose Data Science Fie...read more
  3. 6. Can we use confusion matrix in Linear Regressi...read more

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C5i Data Scientist Interview Process

based on 3 interviews

Interview experience

5
  
Excellent
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C5i Data Scientist Salary
based on 57 salaries
₹4 L/yr - ₹15.8 L/yr
32% less than the average Data Scientist Salary in India
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based on 6 reviews

4.0/5

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3.9

Skill development

3.2

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2.9

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4.4

Job security

3.1

Company culture

2.7

Promotions

3.1

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