HighRadius Data Scientist Interview Questions and Answers

My current work involves analyzing transaction data to identify patterns and trends, which can help PayU optimize their payment processing services.

• Analyzing transaction data to identify fraudulent activities and improve security measures for PayU

• Developing predictive models to forecast transaction volumes and optimize payment processing times

• Utilizing machine learning algorithms to personalize user experiences and inc...read more

I solved a problem by using machine learning algorithms to predict customer churn for a telecom company.

• Identified relevant data sources such as customer demographics, usage patterns, and customer service interactions.

• Preprocessed and cleaned the data to handle missing values and outliers.

• Built and trained a machine learning model using algorithms like logistic regression and random forest.

• Evaluated the model's perform...read more

RNN stands for Recurrent Neural Network and LSTM stands for Long Short-Term Memory. They are types of neural networks used for sequential data processing.

• RNN is a type of neural network that can process sequential data by maintaining a memory of past inputs.

• LSTM is a type of RNN that can handle the vanishing gradient problem and can remember long-term dependencies.

• LSTM has gates that control the flow of information int...read more

Precision and recall are two important metrics used to evaluate the performance of a classification model.

• Precision measures the proportion of true positives among all the predicted positives.

• Recall measures the proportion of true positives among all the actual positives.

• Precision and recall are inversely related and a trade-off exists between them.

• A high precision means that the model is good at predicting positive ca...read more

Regularisation is a technique used in machine learning to prevent overfitting by adding a penalty term to the loss function.

• Regularisation helps to control the complexity of a model and reduce the impact of irrelevant features.

• It adds a penalty term to the loss function, which encourages the model to have smaller weights.

• There are different types of regularisation techniques such as L1 (Lasso) and L2 (Ridge) regularisa...read more

I expect a supportive work environment, opportunities for growth, and clear communication.

• Clear communication on project goals and expectations

• Opportunities for professional development and growth

• Supportive team environment

• Regular feedback and performance evaluations