Appzen Data Scientist Interview Questions
The questions to prepare for a Appzen Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Build a receipt information extraction pipeline using OCR-aware NER and post-processing to recover key fields from noisy scanned receipts.
AppzenDesign a pipeline to extract entities, events, and actionable signals from noisy financial text.
AppzenExplain why F1 is more informative than accuracy for a fraud model with 97.2% accuracy but only 18% recall on a 1% positive class.
AppzenExplain the difference between precision and recall, and how each reflects a different type of classification error.
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Build an imbalanced binary classifier for card fraud detection using class weighting, resampling, and threshold tuning with PR-focused evaluation.
AppzenExplain a practical process for tuning model hyperparameters using cross-validation and overfitting checks.
AppzenDesign telemetry and monitoring for a production ML pipeline to catch latency, failures, and data quality issues early.
AppzenAssesses your ability to approach an image annotation or computer vision task under interview constraints.
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