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Dunnhumby Data Scientist Interview Questions and Answers

Updated 3 May 2024

Dunnhumby Data Scientist Interview Experiences

1 interview found

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

I applied via Referral and was interviewed before May 2023. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Sql, Python programming Questions
Round 2 - Technical 

(1 Question)

  • Q1. Retail, CPG based case study questions like offer allocation method for loyal customers

Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. What friends think of you?
  • Ans. 

    My friends think of me as reliable, supportive, and always up for a good time.

    • Reliable - always there when they need help or support

    • Supportive - willing to listen and offer advice

    • Fun-loving - enjoys socializing and trying new things

  • Answered by AI

Interview Preparation Tips

Round: Resume Shortlist
Experience: After Resume Shortlist we had an aptitute round.
Tips: Answer according to your own judgement. Dont try to be too precise.

Round: HR Interview
Experience: I said they think I am a workaholic as I prefer to complete my work before chilling with them.

College Name: NIT Durgapur

Interview Preparation Tips

Round: HR Interview
Experience: Interview at 11 pm. Stressed environment, close to stress interview.
SELECTION PROCEDURE:
1.Online Test
2. GD
3. PI(HR)
GD TOPICS :
Topic 1 : How can education system benefit from interdisciplinary methods.
Topic 2 : Interconnected problems in the field of movie making.
INTERVIEW EXPERIENCE:
So you can speak German? Describe MS Dhoni in german. They opened Google Translate to counter check the words they wanted to be translated in both Deutsch and Spanish. Your profile speaks of an inclination towards software skills, why do you want to join an analytics company? Justify your action in two reasons as to why are you sitting here interviewing for the post of a data scientist rather than apply for a software engineer when this CV speaks highly of computer science? What is Finite Element Method? Explain. How relevant is your work in Computer Vision? Breakdown the tagline of Audi and translate accordingly. What is "Technik für Mobel" ? What are your current projects? Answer : Microsoft Xbox Kinect, Gesture Recognition. Counter question : But at Musimga you'd be doing far simpler stuff.? Counter suggestion : Why don't you go for MS?


Tips: Keep your cool during counter questions. Prepare your profile and CV well. Rest all is your hard work and groomed personal talents and acquired skills you learnt over the internet.

Skills: Ability To Cope Up With Stress, Spanish, German, Finite Element Modeling - FEM, Foreign Language
College Name: NIT Raipur
Funny Moments: Another HR enters in the midst of my interview and asks with bewildered amazement : What language is he speaking?
The other HR, "German".

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?
  • 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

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

I applied via Approached by Company

Round 1 - Technical 

(3 Questions)

  • Q1. Explain Transformers how different from previous RNN, LSTM etc.
  • Ans. 

    Transformers are a type of neural network architecture that utilizes self-attention mechanisms to process sequential data.

    • Transformers use self-attention mechanisms to weigh the importance of different input elements, allowing for parallel processing of sequences.

    • Unlike RNNs and LSTMs, Transformers do not rely on sequential processing, making them more efficient for long-range dependencies.

    • Transformers have been shown ...

  • Answered by AI
  • Q2. What are different types of Attention?
  • Ans. 

    Different types of Attention include self-attention, global attention, and local attention.

    • Self-attention focuses on relationships within the input sequence itself.

    • Global attention considers the entire input sequence when making predictions.

    • Local attention only attends to a subset of the input sequence at a time.

    • Examples include Transformer's self-attention mechanism, Bahdanau attention, and Luong attention.

  • Answered by AI
  • Q3. Difference between GPT and BERT model
  • Ans. 

    GPT is a generative model while BERT is a transformer model for natural language processing.

    • GPT is a generative model that predicts the next word in a sentence based on previous words.

    • BERT is a transformer model that considers the context of a word by looking at the entire sentence.

    • GPT is unidirectional, while BERT is bidirectional.

    • GPT is better for text generation tasks, while BERT is better for understanding the cont

  • Answered by AI
Round 2 - HR 

(1 Question)

  • Q1. Difference between Data scientist, ML and AI
  • Ans. 

    Data scientists analyze data to gain insights, machine learning (ML) involves algorithms that improve automatically through experience, and artificial intelligence (AI) refers to machines mimicking human cognitive functions.

    • Data scientists analyze large amounts of data to uncover patterns and insights.

    • Machine learning involves developing algorithms that improve automatically through experience.

    • Artificial intelligence r...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Jul 2022. There were 4 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Don’t add your photo or details such as gender, age, and address in your resume. These details do not add any value.
View all Resume tips
Round 2 - Aptitude Test 

Medium level of question are there in this section

Round 3 - Group Discussion 

Basic level of question are there in this section

Round 4 - Technical 

(2 Questions)

  • Q1. Q. What is joints? Q. What is linear search? Q. What is your hobby?
  • Ans. 

    Joints are connections between bones that allow movement and provide support to the body.

    • Joints are found throughout the body, such as the knee, elbow, and shoulder.

    • They are made up of bones, cartilage, ligaments, and synovial fluid.

    • Joints enable various types of movements, including flexion, extension, rotation, and abduction.

    • Different types of joints include hinge joints, ball-and-socket joints, and pivot joints.

    • Join...

  • Answered by AI
  • Q2. What is joints and what is your hobby?
  • Ans. 

    I'm not sure how joints relate to data science, but my hobby is playing guitar.

    • Joints can refer to the connection between two bones in the body or the way two things are connected or joined together.

    • Playing guitar is a hobby that helps me relax and unwind after a long day of working with data.

    • While seemingly unrelated to data science, playing an instrument can actually improve cognitive function and creativity, which c

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Basic SQL and Java language are enough for the interview

Skills evaluated in this interview

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

I applied via Naukri.com and was interviewed before May 2023. There were 4 interview rounds.

Round 1 - Assignment 

Simple Classification problem with some MCQ questions

Round 2 - Technical 

(1 Question)

  • Q1. Drill down on basic ML techniques
Round 3 - Technical 

(1 Question)

  • Q1. Project Discussion with mind sharpness check
Round 4 - HR 

(1 Question)

  • Q1. About past experience and expectations

Interview Preparation Tips

Topics to prepare for Fractal Analytics Data Scientist interview:
  • Machine Learning
  • Cloud
  • Statistics
  • Python
  • Application Deployment
  • NLP

I applied via Recruitment Consultant and was interviewed in Jun 2021. There were 4 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. 1. Describe one of your projects in detail. 2. Explain Random Forest and other ML models 3. Statistics
  • Ans. 

    Developed a predictive model for customer churn using Random Forest algorithm.

    • Used Python and scikit-learn library for model development

    • Performed data cleaning, feature engineering, and exploratory data analysis

    • Tuned hyperparameters using GridSearchCV and evaluated model performance using cross-validation

    • Random Forest is an ensemble learning method that builds multiple decision trees and combines their predictions

    • Other...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare your projects well and questions around that

Skills evaluated in this interview

I applied via Naukri.com and was interviewed before Aug 2021. There were 4 interview rounds.

Round 1 - Coding Test 

Machine learning MCQ questions. 2 model-building questions.

Round 2 - Technical 

(1 Question)

  • Q1. Basic statistics, concertation of any ML algo based on the project on resume or previous works,
Round 3 - Technical 

(1 Question)

  • Q1. Interview with data science manager. Mostly focuses on projects on your resume.
Round 4 - HR 

(1 Question)

  • Q1. Salary related discussion and basic HR questions.

Interview Preparation Tips

Interview preparation tips for other job seekers - Go through the resume in detail and focus on explaining the projects and algorithms worked on.

I applied via Company Website and was interviewed in Feb 2022. There were 2 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 Resume tips
Round 2 - Aptitude Test 

There were 13 questions
2 was coding and other multiple choice questions
one coding question was wine quality test

Interview Preparation Tips

Interview preparation tips for other job seekers - Advanced ML questions will be there
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Dunnhumby Interview FAQs

How many rounds are there in Dunnhumby Data Scientist interview?
Dunnhumby interview process usually has 2 rounds. The most common rounds in the Dunnhumby interview process are Technical.
What are the top questions asked in Dunnhumby Data Scientist interview?

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

  1. Retail, CPG based case study questions like offer allocation method for loyal c...read more
  2. Sql, Python programming Questi...read more

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Dunnhumby Data Scientist Interview Process

based on 1 interview

Interview experience

5
  
Excellent
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Dunnhumby Data Scientist Salary
based on 38 salaries
₹9.2 L/yr - ₹19 L/yr
10% less than the average Data Scientist Salary in India
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3.3/5

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4.7

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4.3

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3.4

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3.2

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