Sutherland Global Services Data Scientist Intern Interview Questions and Answers

NER training using deep learning

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
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Q2. Scenario based questions
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They gave a span of 3 days to build an AI-powered webapp

Q1. How would you go about learning a new skill
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Q2. Experience in cloud technologies
Ans. 
I have experience working with cloud technologies such as AWS, Azure, and Google Cloud Platform.
• Experience in setting up and managing virtual machines, storage, and networking in cloud environments

• Knowledge of cloud services like EC2, S3, RDS, and Lambda

• Experience with cloud-based data processing and analytics tools like AWS Glue and Google BigQuery
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Q1. Tell me about yourself
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Q2. Project details and challenges faced in the project
Ans. 
Developed a predictive model for customer churn in a telecom company
• Collected and cleaned customer data from various sources

• Performed exploratory data analysis to identify key factors influencing churn

• Built and fine-tuned machine learning models to predict customer churn

• Challenges included imbalanced data, feature engineering, and model interpretability
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Q1. What is random forest
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Random forest is an ensemble learning method used for classification and regression tasks.
• Random forest is a collection of decision trees that are trained on random subsets of the data.

• Each tree in the random forest independently predicts the target variable, and the final prediction is made by averaging the predictions of all trees.

• Random forest is robust to overfitting and noisy data, and it can handle large datasets...read more
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Q2. Bias variance trade off
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Q1. Tell me about your self?
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Q2. What is maths and stats
Ans. 
Maths and stats refer to the study of mathematical concepts and statistical methods for analyzing data.
• Maths involves the study of numbers, quantities, shapes, and patterns.

• Stats involves collecting, analyzing, interpreting, and presenting data.

• Maths is used to solve equations, calculate probabilities, and model real-world phenomena.

• Stats is used to make informed decisions, draw conclusions, and test hypotheses.

• Both ma...read more
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Confusion matrix what are your job rolls explain me Gradient boosting algorithm?

Asked the question about ml and basic python questions

Q1. 1. Basics of Python 2. Basics of ML like supervised and unsupervised learning
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Basic DP, Array Questions

Q1. Resume Walkthrough and Discussion, Medium level coding questions
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Q1. Discussion with Manager
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Q1. Normal HR round
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Easy array questions.

Q1. Explain projects from resume.
Ans. 
Developed a machine learning model to predict customer churn for a telecom company.
• Used Python and scikit-learn to preprocess data and build the model

• Performed feature engineering to improve model performance

• Evaluated model using metrics like accuracy, precision, and recall
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Q2. Questions on image processing and computer vision.
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