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Incedo Data Scientist Interview Questions and Answers

Updated 28 Jun 2024

Incedo Data Scientist Interview Experiences

1 interview found

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-

I applied via Campus Placement

Round 1 - Coding Test 

Test+2 interviews(technical and statistics)

Round 2 - Case Study 

Basic guestimates and case studies

Interview Preparation Tips

Interview preparation tips for other job seekers - Study hard

Interview questions from similar companies

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

Aptitude, coding on python NLP

Round 2 - Group Discussion 

Python Data Frames, String list manipulation

Round 3 - HR 

(2 Questions)

  • Q1. Common discussion
  • Q2. Salary location etc
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Python questions moderate to difficult

Round 2 - One-on-one 

(2 Questions)

  • Q1. Introduction about self
  • Ans. 

    I am a data scientist with a background in statistics and machine learning.

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

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

    • I have worked on projects involving predictive modeling and data visualization.

    • I am passionate about using data to drive business decisions and solve complex problems.

  • Answered by AI
  • Q2. Python basics like list, dictionary
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

SQL, Python and Apti ques

Round 2 - Technical 

(2 Questions)

  • Q1. Have given Python question to print a pattern
  • Q2. Some ML algo questions
Round 3 - HR 

(1 Question)

  • Q1. Why u are looking for job change
  • Ans. 

    Seeking new challenges and growth opportunities in a different environment.

    • Looking for new challenges to enhance my skills and knowledge

    • Seeking growth opportunities that align with my career goals

    • Interested in exploring different work environments and cultures

  • Answered by AI
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

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

Round 1 - Coding Test 

Asked 2 to 3 python coding question...

Interview Preparation Tips

Interview preparation tips for other job seekers - prepare technical round
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-

I applied via Job Portal

Round 1 - One-on-one 

(2 Questions)

  • Q1. What is random forest
  • Ans. 

    Random forest is an ensemble learning method used for classification and regression tasks.

    • Random forest is a collection of decision trees that are trained on random subsets of the data.

    • Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.

    • Random forest is robust to overfitting and noisy data, and can handle large datasets wi...

  • Answered by AI
  • Q2. Explain lasso in feature selection
  • Ans. 

    Lasso is a feature selection technique that penalizes the absolute size of the regression coefficients.

    • Lasso stands for Least Absolute Shrinkage and Selection Operator

    • It adds a penalty term to the regression equation, forcing some coefficients to be exactly zero

    • Helps in selecting the most important features and reducing overfitting

    • Useful when dealing with high-dimensional data

    • Example: In a dataset with multiple feature...

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(1 Question)

  • Q1. Questions on MLP, ML

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

Round 1 - Aptitude Test 
Round 2 - Coding Test 
Round 3 - Aptitude Test 

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare well on conditional probability , python basics, and your resume projects

I applied via Referral and was interviewed in Aug 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 - HR 

(1 Question)

  • Q1. What are the relevant projects in Data science & expertise in whatt all tools & technologies
  • Ans. 

    Relevant projects in Data Science and expertise in tools and technologies

    • Projects: Predictive modeling, Natural Language Processing, Computer Vision, Recommender Systems, Time Series Analysis

    • Tools: Python, R, SQL, Tableau, Hadoop, Spark, TensorFlow, Keras, Scikit-learn

    • Technologies: Machine Learning, Deep Learning, Big Data, Cloud Computing, Data Visualization

  • Answered by AI
Round 3 - Technical 

(1 Question)

  • Q1. He asked only coding question in Python & time duration is less & expectations are pretty unclear .

Interview Preparation Tips

Topics to prepare for Tiger Analytics Data Scientist interview:
  • python
Interview preparation tips for other job seekers - Prepare Python properly & clearly check interviewer expectations

Skills evaluated in this interview

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

I applied via LinkedIn and was interviewed in Feb 2023. There were 6 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 - Coding Test 

Platform HackerEarth
9 Questions
2 Coding Questions on Python based on Dynamic Programming
7 Questions MCQ on Data Science and SQL

Round 3 - Technical 

(1 Question)

  • Q1. Data Science Projects discussion Python Coding by sharing screen
Round 4 - Technical 

(4 Questions)

  • Q1. Data Science Projects Detailed Questions
  • Q2. In Depth Knowledge on any one of your project.
  • Q3. Cross Questioning on Regression, Classfication Problems. Dummy Variable Trap Statistics Questions
  • Q4. Questions on Deep Learning Models working and architecture like RNN Exploding/Vanishing Gradient Problem, Solutions like LSTM, CNN model working and different terminologies used.
Round 5 - Technical 

(1 Question)

  • Q1. Again this round was pure Technical. All questions were on Data Science Projects and scenario based. 2 Questions on Probability and puzzle based.
Round 6 - HR 

(1 Question)

  • Q1. Final Round Discussion about Company's Policies and Roles. Your Expectations from the company, the kind of role you are looking for and why Tiger.

Interview Preparation Tips

Interview preparation tips for other job seekers - Just have knowledge of everything what you have mentioned in your resume, small small details, different terms used often in each model and remember to have working knowledge of each model's architecture.
Be confident with your responses.

Incedo Interview FAQs

How many rounds are there in Incedo Data Scientist interview?
Incedo interview process usually has 2 rounds. The most common rounds in the Incedo interview process are Coding Test and Case Study.
How to prepare for Incedo 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 Incedo. The most common topics and skills that interviewers at Incedo expect are Python, Data Science, Machine Learning, Data Analytics and Data Mining.

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Incedo Data Scientist Interview Process

based on 1 interview

Interview experience

3
  
Average
View more
Incedo Data Scientist Salary
based on 55 salaries
₹7.5 L/yr - ₹16.5 L/yr
18% less than the average Data Scientist Salary in India
View more details

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3.3/5

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2.7

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3.4

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2.6

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3.5

Job security

2.8

Company culture

2.1

Promotions

2.9

Work satisfaction

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