Accenture
Global professional services company with leading capabilities in digital, cloud and security.
4 Rounds
~21 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
•
medium
A client wants to predict customer churn but their dataset is highly imbalanced (99% retain, 1% churn). How do you approach this?
#Imbalanced Data
#Classification
#SMOTE
#Evaluation Metrics
Data Scientist
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Technical
•
medium
Your classification model has a 95% accuracy, but the client is unhappy because it's missing critical fraudulent transactions. What metric should you have optimized instead?
#Evaluation Metrics
#Recall
#Fraud Detection
Data Scientist
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Technical
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easy
What is the curse of dimensionality, and what techniques would you use to overcome it in a high-dimensional client dataset?
#Dimensionality Reduction
#PCA
#Feature Engineering
Machine Learning Engineer
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Technical
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easy
Explain the difference between L1 (Lasso) and L2 (Ridge) regularization. When would you use L1 over L2?
#Regularization
#Linear Models
Machine Learning Engineer
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Technical
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easy
Explain the bias-variance tradeoff. How does it relate to model underfitting and overfitting?
#Model Evaluation
#Theory
Machine Learning Engineer
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Technical
•
medium
Explain how you would perform cross-validation on a time-series forecasting model.
#Time Series
#Cross-Validation
Machine Learning Engineer
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Technical
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easy
If a client wants to minimize false positives in a medical diagnosis model, which evaluation metric should you optimize for?
#Metrics
#Classification
Machine Learning Engineer
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Technical
•
medium
We are building a fraud detection model for a banking client where fraud cases represent only 0.1% of the data. How would you handle this severe class imbalance?
#Imbalanced Data
#Classification
#Sampling
Machine Learning Engineer
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Technical
•
medium
Compare Random Forest and Gradient Boosting Trees. In what scenarios would you choose one over the other?
#Ensemble Methods
#Decision Trees
Difficulty Radar
Based on recent AI-sourced data.
Meet Your Interviewers
The "Standard" Interviewer
Senior EngineerFocuses on core competencies, system constraints, and clear communication.
SimulateUnwritten Rules
Think Out Loud
Always explain your thought process before writing code or drawing architecture.