Shriram General Insurance Data Analyst Interview Questions and Answers

It was moderate level questions

It depends on your group and the topic of discussion

Q1. Why should we hire you?
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Q2. Tell me about yourself.
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Statistics Questions

Q1. Assumptions of Machine Learning
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Assumptions of Machine Learning include data availability, feature relevance, and model interpretability.
• Data availability is crucial for training machine learning models.

• Assumptions about the relevance of features in the data must be made.

• Model interpretability is important for understanding the decisions made by the machine learning model.
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Q1. Previous work discussion
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Q2. Relevant work experience
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Q3. Tools knowledge
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Puzzles
Basic machine learning
Resume project related questions

One case related to insurance
Stress round
Adv ML

Q1. Normal Hr questions
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Q1. Technical ML QUESTIONS
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Q2. PYTHON QUESTIONS
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Q1. 1) Formula for Precision and recall
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Precision = TP / (TP + FP), Recall = TP / (TP + FN)
• Precision is the ratio of correctly predicted positive observations to the total predicted positive observations

• Recall is the ratio of correctly predicted positive observations to the all observations in actual class

• Example: If a model predicts 100 positive cases, out of which 80 are actually positive, precision = 80/100, recall = 80/total actual positive cases
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Q2. 2) Difference between R2 and adjusted R2
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R2 measures the proportion of variance explained by the model, while adjusted R2 adjusts for the number of predictors in the model.
• R2 is the proportion of variance in the dependent variable that is predictable from the independent variables.

• Adjusted R2 penalizes the addition of unnecessary predictors in the model, providing a more accurate measure of the model's goodness of fit.

• R2 can increase even when adding irreleva...read more
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