Ernst & Young Senior Data Scientist Interview Questions, Process, and Tips

Anomaly detection is identifying unusual patterns in data. LSTM is a type of neural network used for sequence prediction. BERT is used in chatbots for natural language processing.

• Anomaly detection involves identifying patterns in data that deviate from the norm

• LSTM is a type of neural network that is used for sequence prediction and can handle long-term dependencies

• BERT is a pre-trained language model used for natural ...read more

Preprocessing techniques include data cleaning, normalization, encoding, and feature scaling. Overfitting can be resolved by using techniques like cross-validation, regularization, and early stopping.

• Data cleaning involves removing missing values, outliers, and duplicates

• Normalization scales the data to a range of 0 to 1

• Encoding converts categorical variables into numerical values

• Feature scaling standardizes the range ...read more

I handle large amount of financial data by using distributed computing and parallel processing.

• Use distributed computing frameworks like Hadoop or Spark to handle large datasets

• Implement parallel processing to speed up data processing

• Use cloud-based solutions like AWS or Azure for scalability

• Optimize data storage and retrieval using compression and indexing techniques

• Ensure data security and compliance with regulations

Outliers can be handled by removing or transforming them. Unbalanced datasets can be handled by resampling techniques.

• For outliers, use statistical methods like z-score or IQR to identify and remove them.

• For unbalanced datasets, use techniques like oversampling, undersampling, or SMOTE to balance the classes.

• For regression problems, use robust regression techniques like Ridge or Lasso to handle outliers.

• For classificat...read more