Upload Button Icon Add office photos
Engaged Employer

i

This company page is being actively managed by Bharat Financial Inclusion Team. If you also belong to the team, you can get access from here

Bharat Financial Inclusion Verified Tick

Compare button icon Compare button icon Compare

Filter interviews by

Bharat Financial Inclusion Data Scientist Interview Questions, Process, and Tips

Updated 6 Sep 2021

Bharat Financial Inclusion Data Scientist Interview Experiences

1 interview found

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 questions from similar companies

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
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Jan 2024.

Round 1 - Technical 

(1 Question)

  • Q1. He asked me to rate my sql and python out of 5 and gave me a scenario and asked to write a sql for it, it was basic left join and case statement question
Round 2 - Technical 

(1 Question)

  • Q1. This round was basically discussion round with the interviewer, he asked me what i work in and what thing do i take care off as a data scientist
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
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
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Recruitment Consulltant and was interviewed before Sep 2023. There was 1 interview round.

Round 1 - Coding Test 

Simple Python Coding Test focused on pandas and sql queries as well

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
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Jan 2024.

Round 1 - Technical 

(1 Question)

  • Q1. He asked me to rate my sql and python out of 5 and gave me a scenario and asked to write a sql for it, it was basic left join and case statement question
Round 2 - Technical 

(1 Question)

  • Q1. This round was basically discussion round with the interviewer, he asked me what i work in and what thing do i take care off as a data scientist

Bharat Financial Inclusion Interview FAQs

What are the top questions asked in Bharat Financial Inclusion Data Scientist interview?

Some of the top questions asked at the Bharat Financial Inclusion Data Scientist interview -

  1. What Type of statistics used In earlier organization to analyse and build mod...read more
  2. How familar with python,SQL,and ml mode...read more
  3. How you handle data when outliers are in dat...read more

Tell us how to improve this page.

Interview Questions from Similar Companies

Muthoot Fincorp Interview Questions
4.5
 • 496 Interviews
Shriram Finance Interview Questions
4.1
 • 337 Interviews
Muthoot Finance Interview Questions
3.6
 • 252 Interviews
IIFL Finance Interview Questions
4.0
 • 244 Interviews
SMFG India Credit Interview Questions
4.0
 • 154 Interviews
L&T Finance Interview Questions
3.9
 • 152 Interviews
Mahindra Finance Interview Questions
4.1
 • 150 Interviews
View all
Bharat Financial Inclusion Data Scientist Salary
based on 4 salaries
₹12.5 L/yr - ₹16.5 L/yr
At par with the average Data Scientist Salary in India
View more details
Loan Officer
196 salaries
unlock blur

₹1.2 L/yr - ₹4.5 L/yr

Divisional Manager
160 salaries
unlock blur

₹5.6 L/yr - ₹15.2 L/yr

Sangam Manager
156 salaries
unlock blur

₹1 L/yr - ₹4.6 L/yr

Branch Credit Manager
150 salaries
unlock blur

₹1.5 L/yr - ₹5 L/yr

HR Executive
143 salaries
unlock blur

₹2.2 L/yr - ₹5 L/yr

Explore more salaries
Compare Bharat Financial Inclusion with

Ujjivan Financial Services

4.3
Compare

Equitas Small Finance Bank

4.5
Compare

Jana Small Finance Bank

3.8
Compare

Spandana Sphoorty Financial

3.8
Compare
Did you find this page helpful?
Yes No
write
Share an Interview