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Netflix Data Scientist Interview Questions and Answers

Updated 21 Sep 2024

Netflix 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 in Aug 2024. There were 3 interview rounds.

Round 1 - Group Discussion 

You must work through a licensed agent, producer, attorney, manager, or industry executive, as appropriate, who already has a relationship with Netflix.

Round 2 - Group Discussion 

A factual group discussion is a formal discussion where participants exchange information and facts on a particular topic. The discussion focuses on presenting and analyzing objective data and information rather than subjective opinions or personal experiences.

Round 3 - Aptitude Test 

Done to measure people's attitudes

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Interview preparation tips for other job seekers - Attend virtual job fairs and industry events or conferences.

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

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

Round 1 - Coding Test 

The assessment consists of a dataset for which we are required to build a machine learning model and submit the results along with code and detailed documentation

Round 2 - Technical 

(3 Questions)

  • Q1. What are ensemble models
  • Ans. 

    Ensemble models are machine learning models that combine multiple individual models to improve predictive performance.

    • Ensemble models work by aggregating predictions from multiple models to make a final prediction.

    • Common types of ensemble models include Random Forest, Gradient Boosting, and AdaBoost.

    • Ensemble models are often more accurate and robust than individual models.

    • They can reduce overfitting and increase genera...

  • Answered by AI
  • Q2. Difference between bagging and boosting
  • Ans. 

    Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.

    • Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

    • Boosting involves training multiple models sequentially, where each subsequent model c...

  • Answered by AI
  • Q3. A lot of tree based questions

Skills evaluated in this interview

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

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

Round 1 - Coding Test 

The assessment consists of a dataset for which we are required to build a machine learning model and submit the results along with code and detailed documentation

Round 2 - Technical 

(3 Questions)

  • Q1. What are ensemble models
  • Ans. 

    Ensemble models are machine learning models that combine multiple individual models to improve predictive performance.

    • Ensemble models work by aggregating predictions from multiple models to make a final prediction.

    • Common types of ensemble models include Random Forest, Gradient Boosting, and AdaBoost.

    • Ensemble models are often more accurate and robust than individual models.

    • They can reduce overfitting and increase genera...

  • Answered by AI
  • Q2. Difference between bagging and boosting
  • Ans. 

    Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.

    • Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

    • Boosting involves training multiple models sequentially, where each subsequent model c...

  • Answered by AI
  • Q3. A lot of tree based questions

Skills evaluated in this interview

Netflix Interview FAQs

How many rounds are there in Netflix Data Scientist interview?
Netflix interview process usually has 3 rounds. The most common rounds in the Netflix interview process are Group Discussion and Aptitude Test.

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Netflix Data Scientist Interview Process

based on 1 interview

Interview experience

5
  
Excellent
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Netflix Data Scientist Salary
based on 13 salaries
₹35.1 L/yr - ₹80.5 L/yr
339% more than the average Data Scientist Salary in India
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Netflix Data Scientist Reviews and Ratings

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5.0/5

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