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Citicorp Data Scientist Interview Questions, Process, and Tips

Updated 19 Apr 2024

Top Citicorp Data Scientist Interview Questions and Answers

  • Q1. Which test is used in logistic regression to check the significance of the variable
  • Q2. What is R square and how R square is different from Adjusted R square
  • Q3. How to check outliers in a variable, what treatment should you use to remove such outliers
View all 9 questions

Citicorp Data Scientist Interview Experiences

3 interviews found

Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-

I was interviewed before Apr 2023.

Round 1 - Technical 

(1 Question)

  • Q1. Basic statistics
Round 2 - Technical 

(1 Question)

  • Q1. Project related

Interview Preparation Tips

Interview preparation tips for other job seekers - Donot join citi....no job security at all...I joined and was thrown in 3months due to their restructuring and budget issues.very bad management

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Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
-

I applied via Company Website and was interviewed before Feb 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. ML concepts , regression, regularization etc

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I applied via Walk-in and was interviewed in Mar 2020. There was 1 interview round.

Interview Questionnaire 

10 Questions

  • Q1. What is R square and how R square is different from Adjusted R square
  • Ans. 

    R square is a statistical measure that represents the proportion of the variance in the dependent variable explained by the independent variables.

    • R square is a value between 0 and 1, where 0 indicates that the independent variables do not explain any of the variance in the dependent variable, and 1 indicates that they explain all of it.

    • It is used to evaluate the goodness of fit of a regression model.

    • Adjusted R square t...

  • Answered by AI
  • Q2. Explain what do u understand by the team WOE and IV. What's the importance. Advantages and disadvantages
  • Q3. What are variable reducing techniques
  • Ans. 

    Variable reducing techniques are methods used to identify and select the most relevant variables in a dataset.

    • Variable reducing techniques help in reducing the number of variables in a dataset.

    • These techniques aim to identify the most important variables that contribute significantly to the outcome.

    • Some common variable reducing techniques include feature selection, dimensionality reduction, and correlation analysis.

    • Fea...

  • Answered by AI
  • Q4. Which test is used in logistic regression to check the significance of the variable
  • Ans. 

    The Wald test is used in logistic regression to check the significance of the variable.

    • The Wald test calculates the ratio of the estimated coefficient to its standard error.

    • It follows a chi-square distribution with one degree of freedom.

    • A small p-value indicates that the variable is significant.

    • For example, in Python, the statsmodels library provides the Wald test in the summary of a logistic regression model.

  • Answered by AI
  • Q5. How to check multicollinearity in Logistic regression
  • Ans. 

    Multicollinearity in logistic regression can be checked using correlation matrix and variance inflation factor (VIF).

    • Calculate the correlation matrix of the independent variables and check for high correlation coefficients.

    • Calculate the VIF for each independent variable and check for values greater than 5 or 10.

    • Consider removing one of the highly correlated variables or variables with high VIF to address multicollinear...

  • Answered by AI
  • Q6. Difference between bagging and boosting
  • Ans. 

    Bagging and boosting are ensemble methods used in machine learning to improve model performance.

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

    • Boosting involves iteratively training models on the same dataset, with each subsequent model focusing on the samples that were misclassified by the previous model.

    • Bagging reduc...

  • Answered by AI
  • Q7. Explain the logistics regression process
  • Ans. 

    Logistic regression is a statistical method used to analyze and model the relationship between a binary dependent variable and one or more independent variables.

    • It is a type of regression analysis used for predicting the outcome of a categorical dependent variable based on one or more predictor variables.

    • It uses a logistic function to model the probability of the dependent variable taking a particular value.

    • It is commo...

  • Answered by AI
  • Q8. Explain Gini coefficient
  • Ans. 

    Gini coefficient measures the inequality among values of a frequency distribution.

    • Gini coefficient ranges from 0 to 1, where 0 represents perfect equality and 1 represents perfect inequality.

    • It is commonly used to measure income inequality in a population.

    • A Gini coefficient of 0.4 or higher is considered to be a high level of inequality.

    • Gini coefficient can be calculated using the Lorenz curve, which plots the cumulati...

  • Answered by AI
  • Q9. Difference between chair and cart
  • Ans. 

    A chair is a piece of furniture used for sitting, while a cart is a vehicle used for transporting goods.

    • A chair typically has a backrest and armrests, while a cart does not.

    • A chair is designed for one person to sit on, while a cart can carry multiple items or people.

    • A chair is usually stationary, while a cart is mobile and can be pushed or pulled.

    • A chair is commonly found in homes, offices, and public spaces, while a c...

  • Answered by AI
  • Q10. How to check outliers in a variable, what treatment should you use to remove such outliers
  • Ans. 

    Outliers can be detected using statistical methods like box plots, z-score, and IQR. Treatment can be removal or transformation.

    • Use box plots to visualize outliers

    • Calculate z-score and remove data points with z-score greater than 3

    • Calculate IQR and remove data points outside 1.5*IQR

    • Transform data using log or square root to reduce the impact of outliers

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Explain the concept properly, if not able to explain properly then take a pause and try again with some examples. Be confident.

Skills evaluated in this interview

Interview questions from similar companies

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
6-8 weeks
Result
Selected Selected

I applied via Campus Placement and was interviewed in Dec 2022. There were 4 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 - Aptitude Test 

Hard level aptitude questions... Time taking sums

Round 3 - Technical 

(2 Questions)

  • Q1. Puzzles and probability questions
  • Q2. Asking completely about data science projects in your resume
Round 4 - HR 

(2 Questions)

  • Q1. Just asked some puzzle questions
  • Q2. Asked if iam willing to relocate and about my family

Interview Preparation Tips

Topics to prepare for IDFC FIRST Bank Data Scientist interview:
  • Data Science
Interview preparation tips for other job seekers - Be strong on your resume and probability questions also with puzzles
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Logistic regression loss function
  • Q2. Step function in ML context
  • Ans. 

    Step function is a function that returns a constant value for a certain range of inputs.

    • In machine learning, step functions are used as activation functions in neural networks.

    • They are typically used in binary classification problems where the output is either 0 or 1.

    • Examples include Heaviside step function and sigmoid step function.

  • Answered by AI

Skills evaluated in this interview

Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(1 Question)

  • Q1. What do you do if your model has higher false positives
  • Ans. 

    Investigate the model performance metrics and adjust the threshold for classification.

    • Analyze the confusion matrix to understand the distribution of false positives.

    • Adjust the threshold for classification to reduce false positives.

    • Consider using different evaluation metrics like precision, recall, and F1 score.

    • Explore feature importance to identify variables contributing to false positives.

  • Answered by AI

Skills evaluated in this interview

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

I applied via Job Portal and was interviewed in Aug 2023. There were 2 interview rounds.

Round 1 - Aptitude Test 

Aptitude test for about an hour.

Round 2 - One-on-one 

(2 Questions)

  • Q1. Questions related to data science were asked based on your resume. Puzzles were asked too. Mostly they were from gfg.
  • Q2. What are parameters used in a random forest.
  • Ans. 

    Parameters used in a random forest include number of trees, maximum depth of trees, minimum samples split, and maximum features.

    • Number of trees: The number of decision trees to be used in the random forest.

    • Maximum depth of trees: The maximum depth allowed for each decision tree.

    • Minimum samples split: The minimum number of samples required to split a node.

    • Maximum features: The maximum number of features to consider when

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Be

Skills evaluated in this interview

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

(2 Questions)

  • Q1. Explain previous projects
  • Q2. Explain 2 algo of your choice

Interview Preparation Tips

Interview preparation tips for other job seekers - No tips just present yourself
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

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

Round 1 - Coding Test 

The first technical round will cover how computer vision works, including the advantages and disadvantages of regression and random forest. It will also include discussions on when to use precision and recall, methods to reduce false positives, and criteria for selecting different models. Additionally, disadvantages of PCA will be addressed, along with project-related questions. The second round will focus on standard aptitude tests, while the third round will involve a casual conversation with the Executive Vice President.

Round 2 - Aptitude Test 

Normal aptitude questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Focus on machine learning concepts, develop strong knowledge in Python programming, and learn about PCA, clustering, cross-validation, and hyperparameter tuning.
Interview experience
3
Average
Difficulty level
Hard
Process Duration
2-4 weeks
Result
No response

I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.

Round 1 - Technical 

(3 Questions)

  • Q1. Explain Sigmoid Function
  • Ans. 

    Sigmoid function is a mathematical function that maps any real value to a value between 0 and 1.

    • Sigmoid function is commonly used in machine learning for binary classification problems.

    • It is defined as f(x) = 1 / (1 + e^(-x)), where e is the base of the natural logarithm.

    • The output of the sigmoid function is always in the range (0, 1).

    • It is used to convert a continuous input into a probability value.

    • Example: f(0) = 0.5

  • Answered by AI
  • Q2. What is a T-test in logistic regression
  • Ans. 

    A T-test in logistic regression is used to determine the significance of individual predictor variables.

    • T-test in logistic regression is used to test the significance of individual coefficients of predictor variables.

    • It helps in determining whether a particular predictor variable has a significant impact on the outcome variable.

    • The null hypothesis in a T-test for logistic regression is that the coefficient of the predi...

  • Answered by AI
  • Q3. How to fit model to an unexplored market
  • Ans. 

    To fit a model to an unexplored market, conduct thorough market research, gather relevant data, identify key variables, test different models, and continuously iterate and refine the model.

    • Conduct thorough market research to understand the dynamics of the unexplored market

    • Gather relevant data on customer behavior, market trends, competition, etc.

    • Identify key variables that may impact the market and model outcomes

    • Test d...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for IDFC FIRST Bank Data Scientist interview:
  • Logistic Regression
  • Banking

Skills evaluated in this interview

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Citicorp Interview FAQs

How many rounds are there in Citicorp Data Scientist interview?
Citicorp interview process usually has 1-2 rounds. The most common rounds in the Citicorp interview process are Technical.
How to prepare for Citicorp 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 Citicorp. The most common topics and skills that interviewers at Citicorp expect are Data Science, Machine Learning, Natural Language Processing, Credit Risk and Data Analytics.
What are the top questions asked in Citicorp Data Scientist interview?

Some of the top questions asked at the Citicorp Data Scientist interview -

  1. Which test is used in logistic regression to check the significance of the vari...read more
  2. What is R square and how R square is different from Adjusted R squ...read more
  3. How to check outliers in a variable, what treatment should you use to remove su...read more

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Citicorp Data Scientist Interview Process

based on 2 interviews

1 Interview rounds

  • Technical Round
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