Barclays Shared Services Interview Questions, Process, and Tips

Q1. Technical on the Regulatory reporting
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Q1. Technical on Regulatory reporting
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Q1. Explain Hadoop architecture?
Ans. 
Hadoop architecture is a distributed computing framework for processing large data sets across clusters of computers.
• Hadoop consists of HDFS (Hadoop Distributed File System) for storage and MapReduce for processing.

• HDFS divides data into blocks and stores them across multiple nodes in a cluster.

• MapReduce is a programming model for processing large data sets in parallel across a distributed cluster.

• Hadoop also includes ...read more
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Q2. Hadoop vs spark difference
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Hadoop is a distributed storage system while Spark is a distributed processing engine.
• Hadoop is primarily used for storing and processing large volumes of data in a distributed environment.

• Spark is designed for fast data processing and can perform in-memory computations, making it faster than Hadoop for certain tasks.

• Hadoop uses MapReduce for processing data, while Spark uses Resilient Distributed Datasets (RDDs) for f...read more
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Maths and general knowledge

Environmental studies

Q1. Tell about yourself
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Q2. Salary expectation
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Q1. What is credit risk
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Credit risk is the risk of loss due to a borrower's failure to repay a loan or meet contractual obligations.
• Credit risk is the risk that a borrower will default on a loan or debt obligation.

• It is the potential loss that a lender may suffer if a borrower fails to make payments.

• Factors that contribute to credit risk include the borrower's credit history, financial stability, and economic conditions.

• Lenders use credit sco...read more
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Q1. What is regression , classification
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Regression is a statistical method to predict continuous outcomes, while classification is used to predict categorical outcomes.
• Regression is used when the target variable is continuous, such as predicting house prices based on features like size and location.

• Classification is used when the target variable is categorical, like predicting whether an email is spam or not based on its content.

• Regression models include lin...read more
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Q2. NLP techniques and text classification algorithms and techniques like word embeddings
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Q1. Hyper parameters for classification algorithms
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Hyper parameters are settings that are set before the learning process begins and affect the learning process itself.
• Hyper parameters are not learned during the training process, but are set before training begins.

• They control the learning process and impact the performance of the model.

• Examples include learning rate, number of hidden layers, and batch size in neural networks.
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Q2. How to improve efficiency of models
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Improving model efficiency involves feature selection, hyperparameter tuning, and ensemble methods.
• Perform feature selection to reduce dimensionality and focus on relevant features

• Optimize hyperparameters using techniques like grid search or random search

• Utilize ensemble methods like bagging or boosting to improve model performance

• Consider using more advanced algorithms like deep learning for complex data patterns
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Q1. General discussion about oneself
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Q1. Your career ,experience, skills will be checked.
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Q1. Various Unix commands and sql queries
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Q2. Unix commands for permissions
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Unix commands for permissions
• chmod - change file mode bits

• chown - change file owner and group

• ls - list directory contents with permissions

• umask - set default file permissions
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