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Bajaj Finance Data Scientist Interview Questions and Answers

Updated 13 Oct 2024

Bajaj Finance Data Scientist Interview Experiences

2 interviews found

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

I was a test in our college of about 45min revolving around aptitude.

Round 2 - Coding Test 

Few basic coding questions.

Round 3 - One-on-one 

(2 Questions)

  • Q1. About linear and logistic regression
  • Q2. About svm and kernels

Data Scientist Interview Questions & Answers

user image Adidas Boota

posted on 24 Jan 2024

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

(1 Question)

  • Q1. Azure Data Lake, Prediction model

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

(2 Questions)

  • Q1. Common ways to evaluate Time Series model
  • Ans. 

    Common ways to evaluate Time Series model include AIC, BIC, RMSE, MAE, ACF, PACF, etc.

    • Use Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to compare models

    • Calculate Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) to assess model accuracy

    • Analyze Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) to check for autocorrelation in residuals

  • Answered by AI
  • Q2. Best ways to handle multicollinearity
  • Ans. 

    Use techniques like feature selection, regularization, PCA, and VIF to handle multicollinearity.

    • Perform feature selection to choose the most relevant variables for the model.

    • Apply regularization techniques like Lasso or Ridge regression to penalize high coefficients.

    • Utilize Principal Component Analysis (PCA) to reduce dimensionality and decorrelate variables.

    • Check for Variance Inflation Factor (VIF) to identify highly

  • Answered by AI
Round 2 - Technical 

(2 Questions)

  • Q1. Write a function taking input as string and output a dictionary which will give key as characters in these string and values as their frequency of occurrence
  • Q2. TF IDF in NLP
  • Ans. 

    TF IDF is a technique used in NLP to measure the importance of a word in a document within a collection of documents.

    • TF IDF stands for Term Frequency-Inverse Document Frequency.

    • It is used to determine how important a word is in a document relative to a collection of documents.

    • TF IDF is calculated by multiplying the term frequency (TF) of a word in a document by the inverse document frequency (IDF) of the word across al...

  • Answered by AI

Skills evaluated in this interview

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
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 Jul 2023. There were 2 interview rounds.

Round 1 - Aptitude Test 

Questions on Prob Stats, ML

Round 2 - One-on-one 

(2 Questions)

  • Q1. Models you have worked on
  • Q2. Internship Experience

I applied via Recruitment Consultant and was interviewed in Mar 2021. There were 4 interview rounds.

Interview Questionnaire 

4 Questions

  • Q1. How familar with python,SQL,and ml models
  • Ans. 

    I am very familiar with Python, SQL, and ML models.

    • I have extensive experience using Python for data analysis and machine learning tasks.

    • I am proficient in writing SQL queries to extract data from databases.

    • I have worked with a variety of ML models, including regression, classification, and clustering.

    • I am familiar with popular ML libraries such as scikit-learn, TensorFlow, and Keras.

    • I have experience with data preproc...

  • Answered by AI
  • Q2. Ml Classification models including type of metrics
  • Ans. 

    ML classification models use various metrics to evaluate performance.

    • Common metrics include accuracy, precision, recall, F1 score, and AUC-ROC.

    • Accuracy measures the proportion of correct predictions.

    • Precision measures the proportion of true positives among all positive predictions.

    • Recall measures the proportion of true positives among all actual positives.

    • F1 score is the harmonic mean of precision and recall.

    • AUC-ROC me...

  • Answered by AI
  • Q3. How you handle data when outliers are in data
  • Ans. 

    Outliers can significantly impact analysis. It's important to identify and handle them appropriately.

    • Visualize the data to identify outliers

    • Consider the source of the outliers and whether they are valid data points

    • Remove outliers if they are invalid or use robust statistical methods that are less sensitive to outliers

    • Document any handling of outliers in the analysis report

  • Answered by AI
  • Q4. What Type of statistics used In earlier organization to analyse and build models
  • Ans. 

    The organization used descriptive and inferential statistics to analyze and build models.

    • Descriptive statistics were used to summarize and describe the data, such as mean, median, and standard deviation.

    • Inferential statistics were used to make predictions and draw conclusions about the population based on the sample data, such as hypothesis testing and regression analysis.

    • The organization may have also used time series...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Through with all statistics knowledge and model algorithms

Skills evaluated in this interview

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

I applied via Referral and was interviewed in Jul 2024. There were 3 interview rounds.

Round 1 - Technical 

(1 Question)

  • Q1. Basic statistics and ML questions.
Round 2 - One-on-one 

(1 Question)

  • Q1. Face to face interview round. Asked me to write codes on paper
Round 3 - HR 

(1 Question)

  • Q1. Good HR, compensation was better
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Common ways to evaluate Time Series model
  • Ans. 

    Common ways to evaluate Time Series model include AIC, BIC, RMSE, MAE, ACF, PACF, etc.

    • Use Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to compare models

    • Calculate Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) to assess model accuracy

    • Analyze Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) to check for autocorrelation in residuals

  • Answered by AI
  • Q2. Best ways to handle multicollinearity
  • Ans. 

    Use techniques like feature selection, regularization, PCA, and VIF to handle multicollinearity.

    • Perform feature selection to choose the most relevant variables for the model.

    • Apply regularization techniques like Lasso or Ridge regression to penalize high coefficients.

    • Utilize Principal Component Analysis (PCA) to reduce dimensionality and decorrelate variables.

    • Check for Variance Inflation Factor (VIF) to identify highly

  • Answered by AI
Round 2 - Technical 

(2 Questions)

  • Q1. Write a function taking input as string and output a dictionary which will give key as characters in these string and values as their frequency of occurrence
  • Q2. TF IDF in NLP
  • Ans. 

    TF IDF is a technique used in NLP to measure the importance of a word in a document within a collection of documents.

    • TF IDF stands for Term Frequency-Inverse Document Frequency.

    • It is used to determine how important a word is in a document relative to a collection of documents.

    • TF IDF is calculated by multiplying the term frequency (TF) of a word in a document by the inverse document frequency (IDF) of the word across al...

  • Answered by AI

Skills evaluated in this interview

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
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 Jul 2023. There were 2 interview rounds.

Round 1 - Aptitude Test 

Questions on Prob Stats, ML

Round 2 - One-on-one 

(2 Questions)

  • Q1. Models you have worked on
  • Q2. Internship Experience

Bajaj Finance Interview FAQs

How many rounds are there in Bajaj Finance Data Scientist interview?
Bajaj Finance interview process usually has 2 rounds. The most common rounds in the Bajaj Finance interview process are Technical, Aptitude Test and Coding Test.
How to prepare for Bajaj Finance 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 Bajaj Finance. The most common topics and skills that interviewers at Bajaj Finance expect are Computer Vision, Machine Learning, Predictive Analytics, Python and Risk Analytics.
What are the top questions asked in Bajaj Finance Data Scientist interview?

Some of the top questions asked at the Bajaj Finance Data Scientist interview -

  1. about linear and logistic regress...read more
  2. Azure Data Lake, Prediction mo...read more
  3. about svm and kern...read more

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Bajaj Finance Data Scientist Salary
based on 31 salaries
₹6.5 L/yr - ₹20 L/yr
12% less than the average Data Scientist Salary in India
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Bajaj Finance Data Scientist Reviews and Ratings

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3.2/5

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3.0

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2.3

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3.3

Salary & Benefits

4.2

Job Security

2.7

Company culture

3.0

Promotions/Appraisal

2.8

Work Satisfaction

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