MetLife Data Scientist Interview Questions and Answers

Q1. (interviewer observed that i am nervous. so, he did some small talk, i presume to make me feel comfortable)
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Q2. (after describing a project on my resume) explain recall in plain english? why did you use recall as evaluation metric? how do you calculate recall for mutli-label data? how did you decide the number of hi...read more
Ans. 
Recall is a metric used to measure the ability of a model to find all relevant instances in a dataset.
• Recall is the ratio of true positives to the sum of true positives and false negatives.

• It is used as an evaluation metric to assess the model's ability to identify all positive instances correctly.

• In multi-label data, recall can be calculated for each label separately and then averaged.

• The number of hidden layers and n...read more
Answered by AI
Add your answer
Q3. What is universal approximation theorm?
Ans. 
Universal approximation theorem states that a neural network with a single hidden layer can approximate any continuous function.
• A neural network with a single hidden layer can approximate any continuous function

• It is a fundamental theorem in the field of deep learning

• The theorem applies to a wide range of activation functions

• The number of neurons required in the hidden layer may vary depending on the complexity of the ...read more
Answered by AI
Add your answer
Q4. How does backpropagation in neural networks work?
Ans. 
Backpropagation is a supervised learning algorithm used to train neural networks by adjusting weights to minimize error.
• It involves propagating the error backwards through the network to adjust the weights of the connections between neurons.

• The algorithm uses the chain rule of calculus to calculate the gradient of the error with respect to each weight.

• The weights are then updated using a learning rate and the calculate...read more
Answered by AI
Add your answer
Q5. In what scenarios would you advice me to not use ReLU in my hidden layers?
Ans. 
Avoid ReLU when dealing with negative values or vanishing gradients.
• When dealing with negative values, use Leaky ReLU or ELU instead.

• When facing vanishing gradients, use other activation functions like tanh or sigmoid.

• In some cases, using ReLU in all layers can lead to dead neurons.

• Consider the nature of your data and the problem you are trying to solve before choosing an activation function.
Answered by AI
Add your answer
Q6. Some questions on Named Entitiy Recognition(NER)
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Q1. (after describing a project on my resume) how did the end users use this project? why did you choose to use the techniques/methods that you di? if you don't have labelled data, how would you go about doing...read more
Add your answer
Q2. How will you get the embeddings of long sentences/paragraphs that transformer models like BERT truncate? how will you go about using BERT for such sentences? will you use sentence embeddings or word embedd...read more
Ans. 
To get embeddings of long sentences/paragraphs truncated by BERT, we can use pooling techniques like mean/max pooling.
• We can use pooling techniques like mean/max pooling to get embeddings of truncated sentences/paragraphs.

• We can also use sliding window approach to get embeddings of overlapping segments of the long input.

• For using BERT on such long inputs, we can use sentence embeddings or word embeddings depending on t...read more
Answered by AI
Add your answer
Q3. (after describing a project on my resume) brief all the pre-processing you have done for this multi-label text classification problem!
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Q4. If you were an animal or bird, which one would you want to be and why?
Ans. 
I would want to be a dolphin because of their intelligence, social nature, and ability to swim freely in the ocean.
• Dolphins are known for their high level of intelligence and problem-solving abilities.

• They are highly social animals and live in groups called pods.

• Dolphins have the ability to communicate with each other using a complex system of clicks, whistles, and body movements.

• They are also known for their agility a...read more
Answered by AI
Add your answer
Q5. What makes you angry/frustrated on your teammates or people at work?
Ans. 
Lack of communication, unresponsiveness, and lack of accountability frustrate me.
• Lack of communication: When teammates fail to communicate important information or updates, it hampers the progress of the project.

• Unresponsiveness: When teammates do not respond to emails, messages, or requests in a timely manner, it slows down the workflow and creates bottlenecks.

• Lack of accountability: When teammates do not take respons...read more
Answered by AI
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Q6. Why do you want to join Chubb? [have a genuine answer ready, not a googled one]
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Q7. If you manager/upper-management has asked you to do something in a way that seems stupid to you, how will you tackle this? or will you continue to do it the stupid way?
Ans. 
I would respectfully discuss my concerns with my manager and propose alternative solutions.
• Initiate a conversation with the manager to understand their perspective

• Express concerns and provide logical reasoning for alternative approaches

• Present data or examples to support the proposed solutions

• Maintain a respectful and professional attitude throughout the discussion
Answered by AI
Add your answer
Q8. Why are you looking for new opportunities after only 1 and half years at your current company?
Ans. 
Seeking new opportunities to further develop my skills and contribute to a more challenging and dynamic environment.
• Looking for new challenges and growth opportunities

• Seeking a more dynamic and innovative work environment

• Wanting to work on a wider range of projects and gain diverse experience

• Desire to contribute to a company with a stronger focus on data science

• Exploring opportunities for career advancement and profess
Answered by AI
Add your answer

Q1. Why are you looking for new opportunities or change?
Ans. 
I am looking for new opportunities or change because I want to further develop my skills and contribute to a dynamic and innovative team.
• Seeking new challenges and growth opportunities

• Interested in working with a diverse and talented team

• Want to contribute to innovative projects and make a meaningful impact

• Desire to expand knowledge and skills in data science

• Looking for a company culture that aligns with my values and
Answered by AI
Add your answer
Q2. Why are trying for more offers, when you already have two offers with you?
Ans. 
Exploring more offers to make an informed decision and maximize career growth.
• To evaluate the best fit for my skills, interests, and long-term goals.

• To negotiate better compensation and benefits.

• To gain exposure to different industries, technologies, and projects.

• To expand professional network and opportunities.

• To ensure job security and minimize risks.

• To have a backup option in case one offer falls through.

• To explore ...read more
Answered by AI
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2 question
1. Find the highest stock proce profit in a day.
2. To rollup and aggregate claims at covergae level.

Q1. Salry negotiations
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Q1. Whats is supervised learning
Ans. 
Supervised learning is a type of machine learning where the model is trained on labeled data to make predictions or decisions.
• Uses labeled data for training

• Predicts outcomes based on input features

• Examples include regression and classification algorithms
Answered by AI
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Q2. What is unsupervised learning
Ans. 
Unsupervised learning is a type of machine learning where the model is trained on unlabeled data without any predefined output labels.
• No predefined output labels are provided for the training data

• The model must find patterns and relationships in the data on its own

• Common techniques include clustering and dimensionality reduction

• Examples: K-means clustering, Principal Component Analysis (PCA)
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Q1. LSTM RNN and simple RNN difference
Ans. 
LSTM RNN is a type of RNN that can learn long-term dependencies, while simple RNN struggles with vanishing/exploding gradients.
• LSTM RNN has more complex architecture with memory cells, input, forget, and output gates.

• Simple RNN has a single tanh activation function and suffers from vanishing/exploding gradients.

• LSTM RNN is better at capturing long-term dependencies in sequences.

• Simple RNN is simpler but struggles with
Answered by AI
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Q2. What is lasso regression
Ans. 
Lasso regression is a type of linear regression that uses L1 regularization to prevent overfitting by adding a penalty term to the loss function.
• Lasso regression helps in feature selection by shrinking the coefficients of less important features to zero.

• It is particularly useful when dealing with high-dimensional data where the number of features is much larger than the number of samples.

• The regularization parameter in...read more
Answered by AI
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Q1. How to fine tune a llm model
Ans. 
Fine tuning a LLM model involves adjusting hyperparameters to improve performance.
• Perform grid search or random search to find optimal hyperparameters

• Use cross-validation to evaluate different hyperparameter combinations

• Regularize the model to prevent overfitting

• Adjust learning rate and batch size for better convergence

• Consider using techniques like early stopping to prevent overfitting
Answered by AI
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Q1. Normal discussion
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Q1. Salary negotiation
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Q1. Random Forest Hyperparameters
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Q2. Why deep learning is used over statistical models
Ans. 
Deep learning is used over statistical models for complex, non-linear relationships in data.
• Deep learning can automatically learn hierarchical representations of data, capturing intricate patterns and relationships.

• Statistical models may struggle with high-dimensional data or non-linear relationships, where deep learning excels.

• Deep learning can handle unstructured data like images, audio, and text more effectively tha...read more
Answered by AI
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Q3. How XGB is better than RF
Ans. 
XGB is better than RF due to its ability to handle complex relationships and optimize performance.
• XGB uses gradient boosting which allows for better handling of complex relationships compared to RF

• XGB optimizes performance by using regularization techniques to prevent overfitting

• XGB is faster and more efficient in training compared to RF

• XGB allows for parallel processing which can speed up computation

• XGB has been shown...read more
Answered by AI
Add your answer

Q1. (interviewer observed that i am nervous. so, he did some small talk, i presume to make me feel comfortable)
Add your answer
Q2. (after describing a project on my resume) explain recall in plain english? why did you use recall as evaluation metric? how do you calculate recall for mutli-label data? how did you decide the number of hi...read more
Ans. 
Recall is a metric used to measure the ability of a model to find all relevant instances in a dataset.
• Recall is the ratio of true positives to the sum of true positives and false negatives.

• It is used as an evaluation metric to assess the model's ability to identify all positive instances correctly.

• In multi-label data, recall can be calculated for each label separately and then averaged.

• The number of hidden layers and n...read more
Answered by AI
Add your answer
Q3. What is universal approximation theorm?
Ans. 
Universal approximation theorem states that a neural network with a single hidden layer can approximate any continuous function.
• A neural network with a single hidden layer can approximate any continuous function

• It is a fundamental theorem in the field of deep learning

• The theorem applies to a wide range of activation functions

• The number of neurons required in the hidden layer may vary depending on the complexity of the ...read more
Answered by AI
Add your answer
Q4. How does backpropagation in neural networks work?
Ans. 
Backpropagation is a supervised learning algorithm used to train neural networks by adjusting weights to minimize error.
• It involves propagating the error backwards through the network to adjust the weights of the connections between neurons.

• The algorithm uses the chain rule of calculus to calculate the gradient of the error with respect to each weight.

• The weights are then updated using a learning rate and the calculate...read more
Answered by AI
Add your answer
Q5. In what scenarios would you advice me to not use ReLU in my hidden layers?
Ans. 
Avoid ReLU when dealing with negative values or vanishing gradients.
• When dealing with negative values, use Leaky ReLU or ELU instead.

• When facing vanishing gradients, use other activation functions like tanh or sigmoid.

• In some cases, using ReLU in all layers can lead to dead neurons.

• Consider the nature of your data and the problem you are trying to solve before choosing an activation function.
Answered by AI
Add your answer
Q6. Some questions on Named Entitiy Recognition(NER)
Add your answer

Q1. (after describing a project on my resume) how did the end users use this project? why did you choose to use the techniques/methods that you di? if you don't have labelled data, how would you go about doing...read more
Add your answer
Q2. How will you get the embeddings of long sentences/paragraphs that transformer models like BERT truncate? how will you go about using BERT for such sentences? will you use sentence embeddings or word embedd...read more
Ans. 
To get embeddings of long sentences/paragraphs truncated by BERT, we can use pooling techniques like mean/max pooling.
• We can use pooling techniques like mean/max pooling to get embeddings of truncated sentences/paragraphs.

• We can also use sliding window approach to get embeddings of overlapping segments of the long input.

• For using BERT on such long inputs, we can use sentence embeddings or word embeddings depending on t...read more
Answered by AI
Add your answer
Q3. (after describing a project on my resume) brief all the pre-processing you have done for this multi-label text classification problem!
Add your answer
Q4. If you were an animal or bird, which one would you want to be and why?
Ans. 
I would want to be a dolphin because of their intelligence, social nature, and ability to swim freely in the ocean.
• Dolphins are known for their high level of intelligence and problem-solving abilities.

• They are highly social animals and live in groups called pods.

• Dolphins have the ability to communicate with each other using a complex system of clicks, whistles, and body movements.

• They are also known for their agility a...read more
Answered by AI
Add your answer
Q5. What makes you angry/frustrated on your teammates or people at work?
Ans. 
Lack of communication, unresponsiveness, and lack of accountability frustrate me.
• Lack of communication: When teammates fail to communicate important information or updates, it hampers the progress of the project.

• Unresponsiveness: When teammates do not respond to emails, messages, or requests in a timely manner, it slows down the workflow and creates bottlenecks.

• Lack of accountability: When teammates do not take respons...read more
Answered by AI
Add your answer
Q6. Why do you want to join Chubb? [have a genuine answer ready, not a googled one]
Add your answer
Q7. If you manager/upper-management has asked you to do something in a way that seems stupid to you, how will you tackle this? or will you continue to do it the stupid way?
Ans. 
I would respectfully discuss my concerns with my manager and propose alternative solutions.
• Initiate a conversation with the manager to understand their perspective

• Express concerns and provide logical reasoning for alternative approaches

• Present data or examples to support the proposed solutions

• Maintain a respectful and professional attitude throughout the discussion
Answered by AI
Add your answer
Q8. Why are you looking for new opportunities after only 1 and half years at your current company?
Ans. 
Seeking new opportunities to further develop my skills and contribute to a more challenging and dynamic environment.
• Looking for new challenges and growth opportunities

• Seeking a more dynamic and innovative work environment

• Wanting to work on a wider range of projects and gain diverse experience

• Desire to contribute to a company with a stronger focus on data science

• Exploring opportunities for career advancement and profess
Answered by AI
Add your answer

Q1. Why are you looking for new opportunities or change?
Ans. 
I am looking for new opportunities or change because I want to further develop my skills and contribute to a dynamic and innovative team.
• Seeking new challenges and growth opportunities

• Interested in working with a diverse and talented team

• Want to contribute to innovative projects and make a meaningful impact

• Desire to expand knowledge and skills in data science

• Looking for a company culture that aligns with my values and
Answered by AI
Add your answer
Q2. Why are trying for more offers, when you already have two offers with you?
Ans. 
Exploring more offers to make an informed decision and maximize career growth.
• To evaluate the best fit for my skills, interests, and long-term goals.

• To negotiate better compensation and benefits.

• To gain exposure to different industries, technologies, and projects.

• To expand professional network and opportunities.

• To ensure job security and minimize risks.

• To have a backup option in case one offer falls through.

• To explore ...read more
Answered by AI
Add your answer

2 question
1. Find the highest stock proce profit in a day.
2. To rollup and aggregate claims at covergae level.

Q1. Salry negotiations
Add your answer