Data Science Interview Machine Learning Python R

Citi Bank Data Science Interview Questions

Major corporations around the world are investing time and resources in data science and data scientists. It is a prime industry that is still growing and developing. If you have the qualities of a data scientist, you can find yourself highly valued and well-compensated.

This Citi bank data science interview questions have been shared by one of our contributors Navneet Mishra. He has recently attended the data science role in Citi bank in Pune, India location and got selected. If you are interested in getting a similar job, review these questions to prep for the job interview.

However, besides the general book knowledge, companies are ultimately developing in-house talent. Brush up on your data science skills and invest in developing a solid foundation that your future work can build up.

Citi Bank Data Science Interview QuestionsBased on her experience and memory, he has shared these questions which were asked to her during the interview. He also shared how the interview went on. These Citi Bank Data science questions and patterns will help you clear the interview if you are going for Citi bank. Even these will help if you are going for the data science role with other top data science startups in India and abroad.

Citi Bank Data science interview pattern

The entire interview consists of three rounds and all were the eliminating round. It was one written test followed by the two rounds of interviews. The first interview was purely technical while the next was more of a techno-managerial round where more scenario-based questions were asked.

Citi bank Data Science Written-test

Here you will be getting five sets of questions and you are supposed to solve at least two sections. Although you can solve all the five sections. The time allocated to the written test is 30 minutes.

1. SQL and SAS

The first section was for SQL & SAS and questions were on the easy range. Some of the questions were like-

  • What can be the output of some SQL query
  • Which procedure to use for the random number generation in SQL
  • To get some output on the tables, which query you should write
  • A couple of questions on SQL Joins

2. Modeling

In the modeling section, there were lots of questions regarding the statistics we use for the models. Some of the major areas in the modeling section were related to-

  • What will be the VIF if the R-square is 0.5?
  • In the ROC curve, which attributes resides on the X-axis
  • What is Z-score
  • What is the good range of some statistical measures (names were given)?

3. R

The third section was having questions purely on R. And this was another easy section. The questions on the R section was majorly around the query. Some of the major areas in R were-

  • Writing output of the query
  • Questions around finding and execution of R Function
  • Questions related to data storage
  • Data cleaning questions around the different packages and functions

4. Python

This section was also similar to R-section and just the coding was changed and almost similar concepts were in the case of Python section as well.

5. Machine Learning

Here the questions were majorly related to creating the models and evaluating those. The questions in this machine learning section were around the algorithms and evaluations. Some of those are-

  • Some scenarios are given and based on that we had to select which can be a good model to start
  • Questions around selecting the best model
  • Questions around tuning the model parameter

Citi Bank Data science Interview questions- Round 1 and Round 2

Here are some of the top questions I was asked during the interview process. Apart from all these questions, there were a lot of questions on the project I explained. You might also be asked questions on the written test like how you have solved those, concepts behind those. Following are some of the top data science interview questions which I was asked-

  1. How to find the coefficient in the case of logistic regression
  2. How to tune the random forest model
  3. What are the different techniques to evaluate the logistic regression model?
  4. Let’s say we have created 4 models in case of logistic regression, how to select the best model there
  5. What is the information rate and when we are using it?
  6. What is the loss function and share the equation?
  7. What are bias and variance and how it affects the model
  8. Whether the variance value should be more or less
  9. If a random forest model is giving overfitting issue, how to tackle it
  10. What are the maximum likelihood and the equation behind it
  11. How you can handle the large datasets and create a model on it
  12. You have 4000 features and have to create the model. How you will do feature selection
  13. What is bagging and boosting
  14. What are some of the common challenges you have faced while creating the model?
  15. What are collinearity and multi-collinearity and how it impacts your model

Wrapping it up!

This was my experience with the Citi Bank Data science interview and I have tried to list all the questions which I remember. Fortunately, I was able to make it finally and waiting for the offer.

If you are also trying to go for the data science role in these companies, try the above questions. Also, if you will face any difficulty finding the answer to these questions, comment below and I will help you. Wish you all the best to all the aspiring data scientist! I am sure you will get it soon 😊

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