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Udaan Data Scientist Interview Questions and Answers

Updated 30 Oct 2024

Udaan Data Scientist Interview Experiences

1 interview found

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

(2 Questions)

  • Q1. Tell me about your projects?
  • Q2. How do you approach the project if you are using logistic regression model?
  • Ans. 

    Approach involves data preprocessing, model training, evaluation, and interpretation.

    • Perform data preprocessing such as handling missing values, encoding categorical variables, and scaling features.

    • Split the data into training and testing sets.

    • Train the logistic regression model on the training data.

    • Evaluate the model using metrics like accuracy, precision, recall, and F1 score.

    • Interpret the model coefficients to under...

  • Answered by AI
Round 2 - HR 

(2 Questions)

  • Q1. What are you future goals?
  • Q2. What would you do if your interested field doesnt have any work in the company?
  • Ans. 

    I would seek opportunities to apply my skills in related fields within the company.

    • Explore other departments or teams within the company that may have projects related to my field of interest

    • Offer to collaborate with colleagues in different departments to bring a new perspective to their projects

    • Seek out professional development opportunities to expand my skills and knowledge in related areas

  • Answered by AI

Skills evaluated in this interview

Interview questions from similar companies

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

Questions related to basic coding were asked, and some background on projects and discussions alongside maths and statistics concepts

Round 2 - Technical 

(1 Question)

  • Q1. Questions related to projects done at my previous company
Round 3 - Technical 

(2 Questions)

  • Q1. Questions related to my work at previous company
  • Q2. ML system design use case type of discussion

Interview Preparation Tips

Interview preparation tips for other job seekers - Make sure to be good at coding wrt DSA basics like array, strings, stacks and recursion.
Also practice some level of basic PyTorch stuff and specially Bert architecture (in terms of code)
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
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 - 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
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
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
-
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
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
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Simple mediam DSA style questions around ML

Udaan Interview FAQs

How many rounds are there in Udaan Data Scientist interview?
Udaan interview process usually has 2 rounds. The most common rounds in the Udaan interview process are Technical and HR.
How to prepare for Udaan 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 Udaan. The most common topics and skills that interviewers at Udaan expect are Automation, Computer science, Customer Service, Demand Forecasting and Instrumentation.

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Udaan Data Scientist Interview Process

based on 1 interview

Interview experience

5
  
Excellent
View more
Udaan Data Scientist Salary
based on 17 salaries
₹9.2 L/yr - ₹35 L/yr
53% more than the average Data Scientist Salary in India
View more details

Udaan Data Scientist Reviews and Ratings

based on 4 reviews

3.1/5

Rating in categories

4.0

Skill development

4.3

Work-life balance

3.7

Salary

2.3

Job security

2.9

Company culture

3.2

Promotions

4.0

Work satisfaction

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