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Barclays Shared Services Data Scientist Interview Questions and Answers
Barclays Shared Services Data Scientist Interview Experiences
1 interview found
Anonymous
Selected
I applied via Referral and was interviewed before Aug 2023. There were 2 interview rounds.
(2 Questions)
- Q1. What is regression , classification
- Ans.
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...
- Q2. NLP techniques and text classification algorithms and techniques like word embeddings
(2 Questions)
- Q1. Hyper parameters for classification algorithms
- Ans.
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.
- Q2. How to improve efficiency of models
- Ans.
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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Skills evaluated in this interview
Data Scientist Jobs at Barclays Shared Services
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Interview Questionnaire
1 Question
- Q1. Diffe heilman algorithm
- Ans.
Diffie-Hellman algorithm is a key exchange protocol used to securely exchange cryptographic keys over a public channel.
It is based on the concept of discrete logarithm problem.
It involves two parties, Alice and Bob, who generate their own private and public keys.
The public keys are exchanged and used to generate a shared secret key.
The shared secret key is used for encryption and decryption of messages.
It is widely use...
Skills evaluated in this interview
I appeared for an interview before Jul 2021.
(2 Questions)
- Q1. Model evaluation and performance metrices
- Q2. Explaination of bagging and boosting techniques
- Ans.
Bagging and boosting are ensemble techniques used to improve the accuracy of machine learning models.
Bagging involves training multiple models on different subsets of the training data and then combining their predictions through voting or averaging.
Boosting involves iteratively training models on the same data, with each subsequent model focusing on the samples that the previous models misclassified.
Bagging reduces va...
Interview Preparation Tips
Skills evaluated in this interview
I applied via Naukri.com and was interviewed before Jul 2021. There were 3 interview rounds.
(1 Question)
- Q1. NLP and Computer Vision based Question were asked.
(1 Question)
- Q1. General Questions on Machine Learning and deployments technique
(1 Question)
- Q1. Salary Negotiations and joining discussion
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Interview Questionnaire
1 Question
- Q1. Good knowledge about Machine Learning algorithms and their mathematical structure.
Interview Preparation Tips
Data Scientist Interview Questions & Answers
Optum Global Solutions
Prayank Kulshrestha
posted on 29 Mar 2022
I applied via Naukri.com and was interviewed in Mar 2022. There were 2 interview rounds.
(2 Questions)
- Q1. Question on NER models
- Q2. Question from project
(2 Questions)
- Q1. Critical thinking questions
- Q2. Case studies based questions
Interview Preparation Tips
NER training using deep learning
(2 Questions)
- Q1. Describe the approach taken for assignment
- Ans.
I approach assignments by breaking them down into smaller tasks, setting deadlines, and regularly checking progress.
Break down the assignment into smaller tasks to make it more manageable
Set deadlines for each task to stay on track
Regularly check progress to ensure everything is on schedule
Seek feedback from colleagues or supervisors to improve the quality of work
- Q2. Scenario based questions
Selected
I applied via Referral and was interviewed before Aug 2022. There were 4 interview rounds.
(1 Question)
- Q1. Question related to CNN in details, Different ML algorithms, Questions related to pandas
(1 Question)
- Q1. Question related to MLOps, GitHub
(1 Question)
- Q1. Salary expectations
Interview Preparation Tips
(1 Question)
- Q1. Fundamentals of ML, classical ML
- Ans.
Fundamentals of classical machine learning
Classical machine learning involves algorithms that learn from data and make predictions or decisions.
Common algorithms include linear regression, decision trees, support vector machines, and k-nearest neighbors.
Key concepts include training data, testing data, model evaluation, and hyperparameter tuning.
Classical ML is often used for tasks like classification, regression, clus
(1 Question)
- Q1. Research paper discussion
Skills evaluated in this interview
I applied via Recruitment Consultant and was interviewed in Mar 2021. There were 3 interview rounds.
Interview Questionnaire
2 Questions
- Q1. Super Quick Case Study on Sales
- Q2. Questions on Machine learning Projects in your Resume
Interview Preparation Tips
Other topics: SQL, Excel, Pivot tables
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Barclays Shared Services Data Scientist Interview Process
based on 1 interview
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