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FirstCry Data Scientist Interview Questions and Answers

Updated 2 Mar 2021

FirstCry Data Scientist Interview Experiences

1 interview found

I applied via LinkedIn and was interviewed in Sep 2020. There were 5 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Explain VIF
  • Ans. 

    VIF stands for Variance Inflation Factor, a measure of multicollinearity in regression analysis.

    • VIF is used to detect the presence of multicollinearity in regression analysis.

    • It measures how much the variance of the estimated regression coefficient is increased due to multicollinearity.

    • A VIF value of 1 indicates no multicollinearity, while a value greater than 1 suggests increasing levels of multicollinearity.

    • A commonl...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on the projects that has been done in past

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(2 Questions)

  • Q1. Simple groupby questions in pandas?
  • Q2. Group by questions in SQL?

Interview Preparation Tips

Interview preparation tips for other job seekers - Lot of opportunity for learning within the company

Interview Questionnaire 

1 Question

  • Q1. Basic ML questions and projects
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Company Website and was interviewed in Jan 2024. There were 2 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Transformer models.
Round 2 - Case Study 

Related to Mathematical intuition in Deep learning.

Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
Not Selected
Round 1 - Technical 

(2 Questions)

  • Q1. Basic Recommendation System Questions
  • Q2. A B Testing Questions
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 experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(1 Question)

  • Q1. Explain bagging vs boosting
  • Ans. 

    Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models.

    • 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 corrects the errors made by the previ...

  • Answered by AI
Round 2 - Case Study 

How to judge if the comment is actually describing a product

I applied via Naukri.com and was interviewed in May 2022. There were 3 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 - Technical 

(1 Question)

  • Q1. Normal Data Science questions
Round 3 - HR 

(1 Question)

  • Q1. Salary discussion and HR related queries

Interview Preparation Tips

Interview preparation tips for other job seekers - Technical must be sound. Candidate must brush up technicals thoroughly. They may ask you for coding as well.
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Case Study 

Business Related case study, signed NDA

Round 2 - Technical 

(2 Questions)

  • Q1. Count number of Parameters in BERT
  • Q2. 3 sum array problem

Interview Preparation Tips

Interview preparation tips for other job seekers - NA
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

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

Round 1 - Technical 

(1 Question)

  • Q1. Came for campus. Asked questions around basics of ML namely CV, L1, L2 loss & their assumptions, Boosting and Bagging
Round 2 - One-on-one 

(1 Question)

  • Q1. Gave a case study on solving a NLP problem
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