ThoughtWorks Data Scientist Interview Questions and Answers

Q1. Co-relation coefficient
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Q2. RFM and Decision Tree Model Difference
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RFM analyzes customer behavior, while Decision Trees are predictive models for classification and regression tasks.
• RFM stands for Recency, Frequency, and Monetary value, used for customer segmentation.

• Decision Trees are a machine learning algorithm used for classification and regression tasks.

• RFM helps identify valuable customers; for example, targeting high-frequency buyers for promotions.

• Decision Trees can predict ou...read more
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Q3. Python Dictionary
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Q4. LLM Architecture
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Q1. Data science related areas
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Case study related to semantic search

Q1. Questions based on case study
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Q1. Conceptual Questions on SQL and Python
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Q1. Questions on Python datatypes, class, object, inheritance,
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Q2. Machine learning algorithms
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Machine learning algorithms are used to train models on data to make predictions or decisions.
• Supervised learning algorithms include linear regression, decision trees, and neural networks.

• Unsupervised learning algorithms include clustering and dimensionality reduction.

• Reinforcement learning algorithms involve learning through trial and error.

• Examples of machine learning applications include image recognition, natural l...read more
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Q3. Sql queries and python coding questions
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Q1. Related to project
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Q1. About the project
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Q2. Evaluation metrics in linear regression, Assumption of linear regression,
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Evaluation metrics and assumptions in linear regression
• Evaluation metrics in linear regression include Mean Squared Error (MSE), Root Mean Squared Error (RMSE), R-squared, and Adjusted R-squared.

• Assumptions of linear regression include linearity, independence, homoscedasticity, and normality of residuals.

• Example: MSE = sum((actual - predicted)^2) / n
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Q1. Technical questions ,salary discussion
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Q1. Self introduction.
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Q2. About your project.
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