ICICI Securities Interview Questions, Process, and Tips

Blackrock customer acquisition strategy

Based on the case study, we were asked to share our points and anything that could have been in a better way.

Q1. Machine learning
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Q2. Data structure
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Q1. Basic questions
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Q1. Self introduction .working experience
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Q2. Studies and family background details
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Q3. Current job responsibilities
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Q4. Overall related Key skills
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Q5. What was my last rating in my current position
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Q6. How my salary increment
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Q7. Current CTC in current company
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My current CTC in my current company is confidential.
• I am not comfortable sharing my current CTC as it is confidential.

• I would prefer to focus on discussing my skills and experience relevant to the position.

• I am open to discussing salary expectations for this role.

• I am confident that my salary expectations are in line with industry standards for this position.
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Q8. Expected ctc in fututer company
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Expected CTC will depend on the company's policies and my negotiation skills.
• Expected CTC is subjective and varies from company to company.

• It also depends on the candidate's experience, skills, and negotiation skills.

• I am open to discussing the salary package based on the company's policies and my expectations.

• I am looking for a fair and competitive salary package.

• I am confident that we can come to a mutually beneficia
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Q9. Reason for left from current job
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Q10. What is my goal to achiev this company
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Q1. CRM fundamentals and campaign basics
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Q1. Explain any Data Science project
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Developed a predictive model to forecast customer churn for a telecommunications company.
• Identified key features such as customer tenure, monthly charges, and service usage

• Collected and cleaned data from customer databases

• Built a machine learning model using logistic regression or random forest algorithms

• Evaluated model performance using metrics like accuracy, precision, and recall

• Provided actionable insights to reduce
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Q2. Types of Error in Statistics
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Types of errors in statistics include sampling error, measurement error, and non-sampling error.
• Sampling error occurs when the sample does not represent the population accurately.

• Measurement error is caused by inaccuracies in data collection or measurement instruments.

• Non-sampling error includes errors in data processing, analysis, and interpretation.

• Examples: Sampling error - selecting a biased sample, Measurement err...read more
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Q3. Types of Machine learning models
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Types of machine learning models include supervised learning, unsupervised learning, and reinforcement learning.
• Supervised learning: Models learn from labeled data, making predictions based on past examples (e.g. linear regression, support vector machines)

• Unsupervised learning: Models find patterns in unlabeled data, clustering similar data points together (e.g. k-means clustering, PCA)

• Reinforcement learning: Models le...read more
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Q4. Functions of pandas library, such as get_dummies()
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get_dummies() function in pandas library is used to convert categorical variables into dummy/indicator variables.
• get_dummies() function creates dummy variables for categorical columns in a DataFrame.

• It converts categorical variables into numerical representation for machine learning models.

• Example: df = pd.get_dummies(df, columns=['column_name'])
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