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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 Jul 2021. There were 3 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Use case for insurance domain
  • Ans. 

    Predicting insurance claims using machine learning algorithms.

    • Fraud detection in insurance claims

    • Risk assessment for insurance policies

    • Pricing optimization for insurance products

    • Customer segmentation for targeted marketing

    • Predictive maintenance for insurance assets

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Be prepared with one use case in story telling way

I applied via Campus Placement and was interviewed in Feb 2021. There was 1 interview round.

Interview Questionnaire 

2 Questions

  • Q1. How you will figure out how many WhatsApp user are there in world
  • Ans. 

    Estimating the number of WhatsApp users worldwide requires a combination of data sources and statistical methods.

    • Collect data from WhatsApp's official reports and announcements

    • Use third-party analytics tools to estimate user numbers

    • Analyze demographic and geographic trends to extrapolate global user numbers

    • Consider factors such as population growth and smartphone adoption rates

    • Compare with similar messaging apps to val

  • Answered by AI
  • Q2. Tell me about the how you will tackle a crude data for data analysis
  • Ans. 

    I will start by understanding the data source and its quality, then clean and preprocess the data before performing exploratory data analysis.

    • Understand the data source and its quality

    • Clean and preprocess the data

    • Perform exploratory data analysis

    • Identify patterns and trends in the data

    • Use statistical methods to analyze the data

    • Visualize the data using graphs and charts

    • Iterate and refine the analysis as needed

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Be confident and always try to discuss

Skills evaluated in this interview

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

I applied via Approached by Company and was interviewed before Nov 2023. There were 2 interview rounds.

Round 1 - Aptitude Test 

It was basic with puzzles and sql

Round 2 - Case Study 

Case study about a pharma company entering a new market, customer segmentation and also past projects discussion.

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
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Campus Placement and was interviewed in Jun 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Simple Aptitude questions, Data interpretation and verbal

Round 2 - One-on-one 

(3 Questions)

  • Q1. Basic questions on Data Analytics, Projects mentioned
  • Q2. Code in SQL and python(moderate)
  • Ans. 

    The candidate is asked to code in SQL and Python at a moderate level.

    • Use SQL to query data from databases

    • Use Python to manipulate and analyze data

    • Practice writing SQL queries and Python scripts

  • Answered by AI
  • Q3. Machine Learning
Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-

I applied via Campus Placement

Round 1 - Aptitude Test 

1 hour aptitude test

Round 2 - One-on-one 

(1 Question)

  • Q1. What is one hot encoding
Round 3 - HR 

(1 Question)

  • Q1. What is your long term goal
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

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
View more
Dunnhumby Data Scientist Salary
based on 28 salaries
₹8.5 L/yr - ₹17 L/yr
18% less than the average Data Scientist Salary in India
View more details

Dunnhumby Data Scientist Reviews and Ratings

based on 11 reviews

3.7/5

Rating in categories

3.5

Skill development

4.8

Work-life balance

2.9

Salary

4.5

Job security

4.4

Company culture

3.5

Promotions

3.6

Work satisfaction

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