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Head Digital Works Data Scientist Interview Questions and Answers

Updated 18 Jul 2024

Head Digital Works Data Scientist Interview Experiences

1 interview found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
No response

I applied via LinkedIn and was interviewed in Jan 2024. There were 5 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. Resume based questions on past experience
  • Q2. Case study based questions
Round 2 - Technical 

(3 Questions)

  • Q1. Resume based questions,
  • Q2. Moderate SQL Coding question
  • Q3. Case study based questions
Round 3 - HR 

(1 Question)

  • Q1. General HR related questions
Round 4 - Behavioral 

(1 Question)

  • Q1. Managerial & Aptitude questions
Round 5 - Behavioral 

(1 Question)

  • Q1. Managerial discussion about role & industry

Interview questions from similar companies

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 Sep 2024. There was 1 interview round.

Round 1 - One-on-one 

(2 Questions)

  • Q1. Explain all of decision tree and random forest?
  • Ans. 

    Decision tree is a tree-like model of decisions and their possible consequences, while random forest is an ensemble learning method that builds multiple decision trees and merges them together.

    • Decision tree is a flowchart-like structure where each internal node represents a decision based on an attribute, each branch represents the outcome of the decision, and each leaf node represents a class label.

    • Random forest is a ...

  • Answered by AI
  • Q2. Some basic probability questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Keep statistics strong

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Probability ,deep learning basics ,machine learning ,simple python programming questions.
  • Ans. It will be multilpe choice questions .Duration - 40 minutes.
  • Answered Anonymously
Round 2 - interview 

(1 Question)

  • Q1. Why this company ,work related to your project,some technical questions on deep learning.
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Describe LSTM and GRU
  • Ans. 

    LSTM and GRU are types of recurrent neural networks used for processing sequential data.

    • LSTM (Long Short-Term Memory) networks are capable of learning long-term dependencies in data.

    • GRU (Gated Recurrent Unit) networks are simpler than LSTM and have fewer parameters.

    • LSTM has three gates (input, output, forget) while GRU has two gates (update, reset).

    • LSTM is better at capturing long-term dependencies but is more complex,...

  • Answered by AI
  • Q2. Define Hypothesis Testing
  • Ans. 

    Hypothesis testing is a statistical method used to make inferences about a population based on sample data.

    • Hypothesis testing involves formulating a null hypothesis and an alternative hypothesis.

    • It aims to determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis.

    • Common methods of hypothesis testing include t-tests, chi-square tests, and ANOVA.

    • The p-value is used to dete...

  • Answered by AI

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

Test 45 mins 30 ques

Round 2 - One-on-one 

(3 Questions)

  • Q1. What is Linearregression
  • Ans. 

    Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.

    • Linear regression is used to predict the value of a dependent variable based on the value of one or more independent variables.

    • It assumes a linear relationship between the independent and dependent variables.

    • The goal of linear regression is to find the best-fitting line that minimi...

  • Answered by AI
  • Q2. 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 it can handle large datasets...

  • Answered by AI
  • Q3. WHat is xgboost
  • Ans. 

    XGBoost is an optimized distributed gradient boosting library designed for efficient and accurate large-scale machine learning.

    • XGBoost stands for eXtreme Gradient Boosting.

    • It is a popular machine learning algorithm known for its speed and performance.

    • XGBoost is used for regression, classification, ranking, and user-defined prediction problems.

    • It is based on the gradient boosting framework and uses decision trees as bas...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Thanks

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Job Portal and was interviewed in Jun 2024. There were 2 interview rounds.

Round 1 - Aptitude Test 

Mcq based test on data science concepts

Round 2 - One-on-one 

(2 Questions)

  • Q1. Explain precision,recall etc
  • Ans. 

    Precision and recall are metrics used to evaluate the performance of classification models.

    • Precision is the ratio of correctly predicted positive observations to the total predicted positive observations.

    • Recall is the ratio of correctly predicted positive observations to the all observations in actual class.

    • F1 score is the weighted average of precision and recall, where the best value is 1 and the worst is 0.

    • Precision ...

  • Answered by AI
  • Q2. What is dropout in neural networks
  • Ans. 

    Dropout is a regularization technique used in neural networks to prevent overfitting by randomly setting some neuron outputs to zero during training.

    • Dropout is a regularization technique used in neural networks to prevent overfitting.

    • During training, a fraction of neurons are randomly selected and their outputs are set to zero.

    • This helps prevent complex co-adaptations in neurons and improves generalization.

    • Dropout is t...

  • Answered by AI
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

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

Round 1 - Aptitude Test 

It been for 45 mins. question asked from python,ML,Deep learning and maths.

Round 2 - Technical 

(1 Question)

  • Q1. 1) explain correlation and convaraince 2) how logistic differ from linear regression
  • Ans. 

    Correlation measures the strength and direction of a linear relationship between two variables, while covariance measures the extent to which two variables change together.

    • Correlation ranges from -1 to 1, where 1 indicates a perfect positive relationship, -1 indicates a perfect negative relationship, and 0 indicates no relationship.

    • Covariance can be positive, negative, or zero. A positive covariance indicates that as o...

  • Answered by AI
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. Basic ML/DL and statistics questions
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Create data frame, make histogram

Interview Preparation Tips

Interview preparation tips for other job seekers - Logistic regression

I applied via Naukri.com and was interviewed in Feb 2021. There was 1 interview round.

Interview Questionnaire 

1 Question

  • Q1. About yourself, your current project, Skillset you have, question related Excel.

Interview Preparation Tips

Interview preparation tips for other job seekers - HR is very unprofessional, she shortlisted people on their English speaking skills for a technical role she sent me wrong meeting invite twice and when I called her after week she told me I was not shortlisted.
Than why the short listed mail was sent ?
If you are applying make sure you have some internal links

Head Digital Works Interview FAQs

How many rounds are there in Head Digital Works Data Scientist interview?
Head Digital Works interview process usually has 5 rounds. The most common rounds in the Head Digital Works interview process are Technical, Behavioral and HR.
How to prepare for Head Digital Works 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 Head Digital Works. The most common topics and skills that interviewers at Head Digital Works expect are Python, SQL, Deployment, Gaming and Career Development.
What are the top questions asked in Head Digital Works Data Scientist interview?

Some of the top questions asked at the Head Digital Works Data Scientist interview -

  1. Managerial & Aptitude questi...read more
  2. Case study based questi...read more
  3. Resume based questio...read more

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Head Digital Works Data Scientist Interview Process

based on 1 interview

Interview experience

4
  
Good
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Head Digital Works Data Scientist Salary
based on 14 salaries
₹13.8 L/yr - ₹26 L/yr
42% more than the average Data Scientist Salary in India
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