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Concentrix Catalyst Data Scientist Interview Questions and Answers

Updated 18 Dec 2022

Concentrix Catalyst Data Scientist Interview Experiences

1 interview found

Interview experience
1
Bad
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Naukri.com and was interviewed in Nov 2022. There were 3 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Technical 

(2 Questions)

  • Q1. How tfidf works in NLP
  • Ans. 

    TF-IDF is a statistical measure used to evaluate the importance of a word in a document.

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

    • It is used to weigh a word's importance in a document by considering its frequency in the document and across all documents

    • The formula for TF-IDF is: TF-IDF = TF * IDF

    • TF (Term Frequency) measures how frequently a term appears in a document

    • IDF (Inverse Document Frequency) mea...

  • Answered by AI
  • Q2. What is the difference between group by and window function in sql
  • Ans. 

    Group by is used to group data based on a column while window function is used to perform calculations on a specific window of data.

    • Group by is used to aggregate data based on a specific column

    • Window function is used to perform calculations on a specific window of data

    • Group by is used with aggregate functions like sum, count, avg, etc.

    • Window function is used with analytical functions like rank, lead, lag, etc.

    • Group by ...

  • Answered by AI
Round 3 - Technical 

(2 Questions)

  • Q1. Tell me about the project you worked on 4 years back
  • Ans. 

    Developed a predictive model to forecast customer churn for a telecom company.

    • Used machine learning algorithms like logistic regression and random forest.

    • Preprocessed and cleaned the dataset by handling missing values and outliers.

    • Performed feature engineering to create new variables for better model performance.

    • Evaluated model performance using metrics like accuracy, precision, and recall.

    • Implemented the model in prod

  • Answered by AI
  • Q2. Why are you leaving your current company
  • Ans. 

    Seeking new challenges and opportunities for growth.

    • Looking for a more challenging role that aligns with my career goals.

    • Seeking a company that values innovation and encourages professional development.

    • Want to work in a more collaborative and diverse team environment.

    • Desire to explore new technologies and industries.

    • Current company lacks opportunities for advancement or career growth.

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - They took my resume from Naukri and contacted me, and 1st round of interview was scheduled. Questions were mostly based on projects in the resume, basics of machine learning, statistics, and hypothesis testing.
The recruiter said that you are selected for 2nd round and this will be with the Vice president.
That vice president did not have any time sense and the interview was scheduled at 10:30 in the night and he joined at 10:45, he started asking about the projects which was done 4 years ago(which was not stall mentioned in the resume). Later started asking about the current project.

Then he asked how did you do hyperparameter tuning, I said using GridSearchCV, he asked did you not use scikit-learn?. He does not even know that GridSerachCv is one of the class inside scikit-learn.

Later I contacted recruiter, she started ignoring my calls, after trying for 5 times, I asked did you get any feedback,? she said still I have not got. How much time they want to say if I am selected for the next round or rejected? I said even if I am not selected, please inform me. But still she has not said anything.

Skills evaluated in this interview

Interview questions from similar companies

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

(3 Questions)

  • Q1. Difference between bagging and boosting
  • Ans. 

    Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.

    • Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

    • Boosting involves training multiple models sequentially, where each subsequent model c...

  • Answered by AI
  • Q2. Parameters of Decision Tree
  • Ans. 

    Parameters of a Decision Tree include max depth, min samples split, criterion, and splitter.

    • Max depth: maximum depth of the tree

    • Min samples split: minimum number of samples required to split an internal node

    • Criterion: function to measure the quality of a split (e.g. 'gini' or 'entropy')

    • Splitter: strategy used to choose the split at each node (e.g. 'best' or 'random')

  • Answered by AI
  • Q3. Explain any one of your project in detail
  • Ans. 

    Developed a predictive model to forecast customer churn in a telecom company

    • Collected and cleaned customer data including usage patterns and demographics

    • Used machine learning algorithms such as logistic regression and random forest to build the model

    • Evaluated model performance using metrics like accuracy, precision, and recall

    • Provided actionable insights to the company to reduce customer churn rate

  • Answered by AI

Skills evaluated in this interview

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

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

Round 1 - One-on-one 

(1 Question)

  • Q1. Basic ML questions based on your project, python basic questions
Round 2 - Coding Test 

Basic python questions on pandas,numpy, and basic SQL questions on windows function like lag

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Aug 2024. There were 2 interview rounds.

Round 1 - Coding Test 

*****, arjumpudi satyanarayana

Round 2 - Technical 

(5 Questions)

  • Q1. What is the python language
  • Ans. 

    Python is a high-level programming language known for its simplicity and readability.

    • Python is widely used for web development, data analysis, artificial intelligence, and scientific computing.

    • It emphasizes code readability and uses indentation for block delimiters.

    • Python has a large standard library and a vibrant community of developers.

    • Example: print('Hello, World!')

    • Example: import pandas as pd

  • Answered by AI
  • Q2. What is the code problems
  • Ans. 

    Code problems refer to issues or errors in the code that need to be identified and fixed.

    • Code problems can include syntax errors, logical errors, or performance issues.

    • Examples of code problems include missing semicolons, incorrect variable assignments, or inefficient algorithms.

    • Identifying and resolving code problems is a key skill for data scientists to ensure accurate and efficient data analysis.

  • Answered by AI
  • Q3. What is the python code
  • Ans. 

    Python code is a programming language used for data analysis, machine learning, and scientific computing.

    • Python code is written in a text editor or an integrated development environment (IDE)

    • Python code is executed using a Python interpreter

    • Python code can be used for data manipulation, visualization, and modeling

  • Answered by AI
  • Q4. What is the project
  • Ans. 

    The project is a machine learning model to predict customer churn for a telecommunications company.

    • Developing predictive models using machine learning algorithms

    • Analyzing customer data to identify patterns and trends

    • Evaluating model performance and making recommendations for reducing customer churn

  • Answered by AI
  • Q5. What is the lnderssip
  • Ans. 

    The question seems to be incomplete or misspelled.

    • It is possible that the interviewer made a mistake while asking the question.

    • Ask for clarification or context to provide a relevant answer.

  • Answered by AI

Interview Preparation Tips

Topics to prepare for IBM Data Scientist interview:
  • Python
  • Machine Learning
Interview preparation tips for other job seekers - No

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Not Selected

I applied via Naukri.com and was interviewed in Sep 2024. There were 2 interview rounds.

Round 1 - Technical 

(3 Questions)

  • Q1. Overfitting and Underfitting
  • Q2. Find Nth-largest element
  • Ans. 

    Find Nth-largest element in an array

    • Sort the array in descending order

    • Return the element at index N-1

  • Answered by AI
  • Q3. NLP Data preprocessing
Round 2 - HR 

(2 Questions)

  • Q1. Salary Discussion
  • Q2. Fitment discussion

Skills evaluated in this interview

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

I applied via Naukri.com and was interviewed in Jul 2024. There were 2 interview rounds.

Round 1 - One-on-one 

(3 Questions)

  • Q1. Tell me about yourself?
  • Ans. 

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

    • Background in statistics and machine learning

    • Experience in solving complex problems using data-driven approaches

    • Passionate about leveraging data to drive insights and decision-making

  • Answered by AI
  • Q2. Describe in detail about one of my main project.
  • Ans. 

    Developed a predictive model for customer churn in a telecom company.

    • Collected and cleaned customer data including usage patterns and demographics.

    • Used machine learning algorithms such as logistic regression and random forest to build the model.

    • Evaluated model performance using metrics like accuracy, precision, and recall.

    • Implemented the model into the company's CRM system for real-time predictions.

  • Answered by AI
  • Q3. Few questions related to my projects.
Round 2 - Technical 

(1 Question)

  • Q1. Questions on Basics python(Since i am fresher)

Interview Preparation Tips

Interview preparation tips for other job seekers - Overall, it was a good experience for me. Very friendly interviewers. I couldn't make it after the second round. I came to know where I was lacking.
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(3 Questions)

  • Q1. Questions around the previous work
  • Q2. Questions around how re-rank work, and image segmentation,
  • Q3. Questions with podman and docker

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare your profile and brush up your knowledge
Interview experience
5
Excellent
Difficulty level
-
Process Duration
Less than 2 weeks
Result
-

I was interviewed in Aug 2024.

Round 1 - Technical 

(2 Questions)

  • Q1. DFA Focus :Sorting ,Searching ,Stacks,Queues, HashMaps
  • Q2. Os & cn: Process scheduling, TCP/IP, HTTP basics
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Asked questions related to stats , Senario based. Interviewer was very nice
  • Q2. Asked questions on Python Programming and asked for Programs Like How can update List , Asked to Build a Tough Dict , Class etc.
Round 2 - HR 

(2 Questions)

  • Q1. Why u want to join?
  • Q2. What is your future goal?
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

Concentrix Catalyst Interview FAQs

How many rounds are there in Concentrix Catalyst Data Scientist interview?
Concentrix Catalyst interview process usually has 3 rounds. The most common rounds in the Concentrix Catalyst interview process are Technical and Resume Shortlist.
What are the top questions asked in Concentrix Catalyst Data Scientist interview?

Some of the top questions asked at the Concentrix Catalyst Data Scientist interview -

  1. what is the difference between group by and window function in ...read more
  2. how tfidf works in ...read more

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Concentrix Catalyst Data Scientist Interview Process

based on 1 interview

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Concentrix Catalyst Data Scientist Salary
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₹5.8 L/yr - ₹17.5 L/yr
20% less than the average Data Scientist Salary in India
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