Equitas Small Finance Bank Assistant Manager II Interview Questions and Answers

Q1. Life insurance business
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Q2. Mutual fund business
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Q1. Why leave previous job.
Ans. 
Seeking new challenges and growth opportunities.
• Desire for career advancement

• Seeking new challenges

• Opportunity for professional growth

• Company restructuring or downsizing

• Relocation to a new area
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Q2. Portfolio size
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Best banking industry

Q1. Best HR manager support
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Q2. Best banking industry for HR manager support
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Q3. And joining formalities
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Best group discussion HR team

Q1. Best' knowledge services
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Best case study structure

Q1. Best banking technical support
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Best' knowledge services of Branch banking activities

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Below company related questions

Best banking industry in TPP

Best banking technical support and achieving Retail asset Target

Q1. Best banking HR policy
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Q1. What were you looking last organisation.
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Q2. Banking products knowledge
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Q3. Customer handling, sales Banking products.
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Financial related. Banking related questions.

Q1. Manager and zonel manager interview
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Q2. What is location and work
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Generic GD topic. My topic was 'Is social media good or bad?'

Q1. Tell me about yourself.
Ans. 
Experienced professional with a background in retail management and a proven track record of driving sales and improving team performance.
• Over 5 years of experience in retail management

• Strong leadership skills demonstrated through successful team management

• Proven ability to increase sales and meet targets

• Excellent communication and interpersonal skills

• Passionate about delivering exceptional customer service
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Q2. Are you open to travel to rural areas for sales?
Ans. 
Yes, I am open to travel to rural areas for sales as it allows me to reach a wider customer base and understand diverse market needs.
• I have previous experience traveling to rural areas for sales in my current role.

• I believe that reaching out to customers in rural areas is essential for expanding the business.

• I am willing to travel to rural areas to meet sales targets and build strong customer relationships.
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Q1. Concepts of class, polymorphism, what are decorators, concepts of inheritance.
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Q2. Difference between bagging and boosting
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Bagging and boosting are ensemble learning techniques used in machine learning to improve the performance of models by combining multiple weak learners.
• Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

• Boosting involves training multiple models sequentially, where each subsequent mode...read more
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Q3. Python coding question to find the employee with second largest income
Ans. 
Python code to find the employee with second largest income in a list of employees
• Sort the list of employees by income in descending order

• Return the employee at index 1 in the sorted list
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Q4. Detect the unique characters in the substring and their length
Ans. 
The candidate needs to identify unique characters in a given substring and calculate their length.
• Iterate through the substring and store each character in a set to keep track of unique characters

• Calculate the length of the set to determine the number of unique characters

• Return the set of unique characters and their length as an array of strings
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Q5. Concepts of mutable and immutable in python.
Ans. 
In Python, mutable objects can be changed after creation, while immutable objects cannot be changed.
• Mutable objects: lists, dictionaries, sets

• Immutable objects: strings, tuples, numbers

• Example: x = [1, 2, 3] (mutable), y = 'hello' (immutable)
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Q1. What is confidence interval of an estimator?
Ans. 
Confidence interval of an estimator is a range of values that is likely to contain the true value of the parameter being estimated.
• Confidence interval provides a range of values within which we are confident the true parameter value lies.

• It is calculated based on the sample data and the desired level of confidence.

• For example, a 95% confidence interval for the mean weight of a population would be a range of values with...read more
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Q2. How logistic regression works for multiple class classification?
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Logistic regression works by calculating the probability of each class and assigning the observation to the class with the highest probability.
• Logistic regression calculates the probability of each class using the logistic function.

• The model then assigns the observation to the class with the highest probability.

• It is commonly used for binary classification, but can be extended to multiple classes using techniques like
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Q3. How do you deal with missing values in a data?
Ans. 
I handle missing values by identifying them, deciding on a strategy (imputation or deletion), and documenting the process.
• Identify missing values by checking for null values or using descriptive statistics.

• Decide on a strategy for handling missing values such as imputation (mean, median, mode) or deletion (row or column).

• Document the process of handling missing values to ensure transparency and reproducibility.
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