TCS
Large multinational IT services and consulting enterprise based in India.
3 Rounds
~14 Days
Medium
The Interview Loop
Recruiter Screen (30 min)
Standard fit check, behavioral questions, and resume overview.
Technical Loop (3-4 Rounds)
Deep dive into domain knowledge, coding, and system design.
Interview Question Bank
Data Scientist
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Technical
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medium
How does XGBoost handle missing values internally?
#XGBoost
#Missing Data
#Algorithms
Data Scientist
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Technical
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easy
Explain the difference between Bagging and Boosting. Give an example of an algorithm for each.
#Ensemble Methods
#Random Forest
#XGBoost
Data Scientist
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Technical
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medium
Given a massive transactional dataset from a banking client, how would you handle highly imbalanced classes for a fraud detection model?
#Imbalanced Data
#SMOTE
#Class Weights
#Fraud Detection
Data Scientist
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Technical
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hard
Explain the mathematical difference between L1 (Lasso) and L2 (Ridge) regularization. Why does L1 lead to sparsity?
#Regularization
#Mathematics
#Feature Selection
Data Scientist
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Technical
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medium
What is Data Leakage in machine learning? Give an example of how it might occur in a time-series forecasting project.
#Data Leakage
#Time Series
#Cross-validation
Data Scientist
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Technical
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medium
What is the curse of dimensionality, and how do you mitigate it in a dataset with 5000 features?
#Dimensionality Reduction
#PCA
#Feature Engineering
Data Scientist
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Technical
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easy
Explain the difference between Precision and Recall. In a medical diagnosis model for a fatal disease, which one is more important?
#Evaluation Metrics
#Classification
Data Scientist
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Technical
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easy
How does the K-Means clustering algorithm work? How do you choose the optimal number of clusters?
#Clustering
#K-Means
#Unsupervised Learning
Data Scientist
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Technical
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medium
What is the difference between Generative and Discriminative models? Give an example of each.
#Model Types
#Generative AI
#Statistics
Machine Learning Engineer
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Technical
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medium
Explain the mathematical difference between L1 (Lasso) and L2 (Ridge) regularization. Why does L1 lead to sparsity?
#Regularization
#Mathematics
#Feature Selection
Machine Learning Engineer
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Technical
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medium
For a BFSI client, we are building a credit card fraud detection model where the fraud rate is 0.01%. How do you handle this severe class imbalance?
#Imbalanced Data
#Classification
#SMOTE
Machine Learning Engineer
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Technical
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medium
Explain the internal working of XGBoost. How does it differ from a Random Forest algorithm?
#Ensemble Methods
#Decision Trees
#Gradient Boosting
Machine Learning Engineer
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Technical
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hard
What is the 'Curse of Dimensionality'? Explain the mathematics behind Principal Component Analysis (PCA) and how it mitigates this issue.
#Dimensionality Reduction
#Linear Algebra
#PCA
Machine Learning Engineer
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Technical
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medium
We are clustering customer profiles for a retail client, but we have no ground truth labels. How do you evaluate the quality of your clustering algorithm?
#Unsupervised Learning
#Clustering
#Evaluation Metrics
Machine Learning Engineer
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Technical
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easy
Explain the concepts of Bagging and Boosting. Give one real-world example where you would prefer one over the other.
#Ensemble Methods
#Model Selection
Machine Learning Engineer
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Technical
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medium
Walk me through your exact strategy for tuning hyperparameters for a Gradient Boosting model to prevent overfitting.
#Hyperparameter Tuning
#Optimization
#Overfitting
Machine Learning Engineer
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Technical
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medium
How do you ensure model fairness and mitigate bias in a machine learning model built to approve or reject bank loans?
#AI Ethics
#Bias Mitigation
#Explainable AI
Difficulty Radar
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Senior EngineerFocuses on core competencies, system constraints, and clear communication.
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Always explain your thought process before writing code or drawing architecture.