Barclays Shared Services Data Scientist Interview Questions and Answers

Q1. Difference between CNN and MLP
Ans. 
CNN is used for image recognition while MLP is used for general classification tasks.
• CNN uses convolutional layers to extract features from images while MLP uses fully connected layers.

• CNN is better suited for tasks that require spatial understanding like object detection while MLP is better for tabular data.

• CNN has fewer parameters than MLP due to weight sharing in convolutional layers.

• CNN can handle input of varying
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Q1. Self Intro and projects discussion
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Q2. Feature selection methods
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Feature selection methods help in selecting the most relevant features for building predictive models.
• Feature selection methods aim to reduce the number of input variables to only those that are most relevant.

• Common methods include filter methods, wrapper methods, and embedded methods.

• Examples include Recursive Feature Elimination (RFE), Principal Component Analysis (PCA), and Lasso regression.
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Q1. Central Limit Theorem
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Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
• The Central Limit Theorem is essential in statistics as it allows us to make inferences about a population based on a sample.

• It states that regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distribut...read more
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Q1. Asked about ml algos
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Q1. Types of Chunking in data preparation in RAG
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Q2. How Embedding works in Vector Databases
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Q3. Explain ARIMA model
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Q4. How can we decide to choose Linear Regression for a business problem
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Q1. What is token and it's limit for Open Source LLMs
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Q2. Difference of a Regression and Time Series problem
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Q3. Advantage of LSTM over RNN
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Q4. Performance Metrics for Logistic Regression
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Q1. Explain about how recommendation engine work
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Recommendation engines analyze user data to suggest items based on preferences and behavior.
• Recommendation engines use collaborative filtering to suggest items based on user behavior and preferences.

• They can also use content-based filtering to recommend items similar to ones the user has liked in the past.

• Some recommendation engines combine both collaborative and content-based filtering for more accurate suggestions.

• Ex...read more
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Q1. Different ML Algorithms
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There are various ML algorithms such as linear regression, decision trees, random forests, SVM, KNN, neural networks, etc.
• Linear regression is used for predicting continuous values

• Decision trees and random forests are used for classification and regression

• SVM is used for classification and regression

• KNN is used for classification and regression

• Neural networks are used for complex problems such as image recognition and
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Q2. Python Libraries
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Quant, Reasoning and python based MCQs

Q1. Question on your past work experience. Can go deep down with respect to your prior work experience
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Q2. In what project have you been involved and what were your roles and responsibility
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Q3. Data Science project pipeline ,what components are involved , step by step process
Ans. 
Data science project pipeline involves multiple components and follows a step-by-step process.
• 1. Define the problem statement and objectives of the project.

• 2. Collect and preprocess the data needed for analysis.

• 3. Explore and visualize the data to gain insights.

• 4. Build and train machine learning models to solve the problem.

• 5. Evaluate the models using appropriate metrics.

• 6. Deploy the model into production and monitor...read more
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Q1. Your prior experience and salary expectations
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