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IDFC FIRST Bank Data Scientist Interview Questions, Process, and Tips
Top IDFC FIRST Bank Data Scientist Interview Questions and Answers
- Q1. What is a T-test in logistic regression
- Q2. How to fit model to an unexplored market
- Q3. What are parameters used in a random forest.
IDFC FIRST Bank Data Scientist Interview Experiences
4 interviews found
Debanjali Ghosh
I applied via Naukri.com and was interviewed in Jul 2024. There was 1 interview round.
(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
- 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...
- 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...
Interview Preparation Tips
- Logistic Regression
- Banking
Skills evaluated in this interview
Himani Tokas
(1 Question)
- Q1. Focus was on SQL, projects done so far, Machine Learning and Stats
Anonymous
I applied via Job Portal and was interviewed in Aug 2023. There were 2 interview rounds.
Aptitude test for about an hour.
(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
Interview Preparation Tips
Skills evaluated in this interview
Selected
I applied via campus placement at Indian Institute of Technology (IIT), Kharagpur and was interviewed in Dec 2022. There were 4 interview rounds.
Hard level aptitude questions... Time taking sums
(2 Questions)
- Q1. Puzzles and probability questions
- Q2. Asking completely about data science projects in your resume
(2 Questions)
- Q1. Just asked some puzzle questions
- Q2. Asked if iam willing to relocate and about my family
Interview Preparation Tips
- Data Science
IDFC FIRST Bank interview questions for designations
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Interview questions from similar companies
G R
I applied via Naukri.com and was interviewed in Mar 2024. There were 3 interview rounds.
(3 Questions)
- Q1. Machine learning algorithms.
- Ans.
Machine learning algorithms are tools used to analyze data, identify patterns, and make predictions without being explicitly programmed.
Machine learning algorithms can be categorized into supervised, unsupervised, and reinforcement learning.
Examples of machine learning algorithms include linear regression, decision trees, support vector machines, and neural networks.
These algorithms require training data to learn patte...
- Q2. Credit risk life cycle
- Q3. Pandas related questions
(3 Questions)
- Q1. Steps of developing a credit risk model
- Ans.
Developing a credit risk model involves several steps to assess the likelihood of a borrower defaulting on a loan.
1. Define the problem and objectives of the credit risk model.
2. Gather relevant data such as credit history, income, debt-to-income ratio, etc.
3. Preprocess the data by handling missing values, encoding categorical variables, and scaling features.
4. Select a suitable machine learning algorithm such as logi...
- Q2. Pandas related questions
- Q3. Bagging and Boosting
(3 Questions)
- Q1. Explain AIC and BIC
- Ans.
AIC and BIC are statistical measures used for model selection in the context of regression analysis.
AIC (Akaike Information Criterion) is used to compare the goodness of fit of different models. It penalizes the model for the number of parameters used.
BIC (Bayesian Information Criterion) is similar to AIC but penalizes more heavily for the number of parameters, making it more suitable for model selection when the focus...
- Q2. Difference between xgboost and lightgbm
- Ans.
XGBoost is a popular gradient boosting library while LightGBM is a faster and more memory-efficient alternative.
XGBoost is known for its accuracy and performance on structured/tabular data.
LightGBM is faster and more memory-efficient, making it suitable for large datasets.
LightGBM uses a histogram-based algorithm for splitting whereas XGBoost uses a level-wise tree growth strategy.
- Q3. Bagging and boosting
Skills evaluated in this interview
(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.
Skills evaluated in this interview
I applied via Campus Placement
It was okay as the interview was scheduled on time.
(1 Question)
- Q1. They asked questions in the interview Including Python, Machine learning, SQL, Power BI
Data Scientist Interview Questions & Answers
Jana Small Finance Bank
Kunal Saraswat
posted on 18 Feb 2024
I was interviewed in Jan 2024.
(1 Question)
- Q1. Machine learning questions
Project Discussion on Eye flue detection
Interview Preparation Tips
I applied via Campus Placement and was interviewed in Aug 2023. There was 1 interview round.
Apptitude + two easy level coding questions , behavioural questions,
Interview Preparation Tips
round 2 : HR + technical combined ( asked your past experience with data handelling and tools used , asked some puzzles and gestimates)
GFG for puzzles, apptitude, english, logical resoning
Selected
I applied via Referral and was interviewed before Jul 2023. There were 2 interview rounds.
If else conditions, data merging, datetime conversions, EDA on a sample data set, duplicates removal and missing value imputation
(1 Question)
- Q1. If you have to sell a kids account, how will you Target the customer. What features will you build?
- Ans.
To target customers for a kids account, focus on features like parental controls, educational content, and interactive games.
Implement parental controls to assure parents of child safety online.
Include educational content to attract parents looking for learning opportunities.
Incorporate interactive games to engage children and make the account more appealing.
Offer rewards or incentives for completing educational activi...
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IDFC FIRST Bank Data Scientist Interview Process
based on 4 interviews
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