Swiss Re Quantitative Analyst Interview Questions and Answers

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

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)

Feature engineering is the process of selecting and transforming relevant features from raw data to improve model performance.

• Identify relevant features based on domain knowledge and data exploration

• Transform features to improve their quality and relevance

• Create new features by combining or extracting information from existing features

• Select the most important features using feature selection techniques

• Iterate the proc

I have used logistic regression and decision tree models for classification.

• Logistic regression is a linear model used for binary classification.

• Decision tree is a non-linear model used for multi-class classification.

• Logistic regression is simple and easy to interpret while decision tree can handle non-linear relationships.

• I chose these models based on the nature of the data and the problem at hand.

Tableau Dashboard actions allow users to interact with the data and visualizations by clicking on specific elements.

• Dashboard actions can be used to filter data, highlight specific data points, or navigate to other dashboards.

• There are four types of actions in Tableau: filter, highlight, URL, and parameter.

• For example, a user can click on a bar chart to filter the data in a related table or click on a map to highlight ...read more

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

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

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

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.

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

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

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

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

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

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

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

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

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

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