Persistent Systems Senior Data Scientist Interview Questions and Answers

Q1. What is random forest
Ans. 
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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It was based on logical reasoning and verbal along with speech recognition

Python based basic questions like sort find maximum

Q1. They asked all the questions based on my projects.
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Q1. Simple he procedure
Ans. 
Simple procedure refers to a straightforward and easy-to-follow set of steps or instructions.
• Follow a clear sequence of steps

• Use simple language and visuals if needed

• Ensure the procedure is easy to understand and execute
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HackeRank Test

Q1. Give data classifications with scrubbing techniques.
Ans. 
Data classifications with scrubbing techniques
• Sensitive data: remove or mask personally identifiable information (PII)

• Outliers: remove or correct data points that are significantly different from the rest

• Duplicate data: remove or merge identical data points

• Inconsistent data: correct or remove data points that do not fit the expected pattern

• Invalid data: remove or correct data points that do not make sense or violate co
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Q2. Day to day workings and responsibility for product development
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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. All questions was related to machine learning
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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. Machine learning related questions and the theory of its operation
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