Visa Associate Data Scientist Interview Questions and Answers

1 python and 1 SQL coding along with ML questions mostly related to monitoring and basic ML

1 python code and also related to ML ...the recruiter came with a dataset to solve

Guestimates, project discussions and Case Studies

Project indepth discussion and case study related Fraud Detection

Q1. Aligning own interest with team requirement
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Q1. DBSCAN Clustering
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Q2. How does current work helps solving use cases for PayU
Ans. 
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
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We were trained for 2 weeks on web dev. and data science and were given individual 2 projects, according to the performance on them and a final interview, candidates were selected.

Q1. All about the assignment done
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Q2. Your interest and particular domain you want to work in
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Q1. ML algorithms and basic python coding
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Q1. SQL and Project related
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Q1. Salary discussion
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General DSA with some ds questions

Q1. Walk through resume
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Q2. Reverse linked list
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Q3. Use of oops in some cases
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Q1. SQL and background related questions
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Q1. What is rnn and lstm
Ans. 
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
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Q2. What is precision and recall
Ans. 
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
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Q3. What is regularisation
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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
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Q1. Basic ML questions you can get those on any website by searching ML/Ds question
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Q2. Some deep question on python like unpacking in python etc
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