Steampunk Data Scientist Interview Questions
The questions to prepare for a Steampunk Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Build and compare baseline and engineered-feature classifiers for consumer loan default prediction, and explain how feature engineering changes model performance.
SteampunkBuild an imbalanced binary classifier for card fraud detection using class weighting, resampling, and threshold tuning with PR-focused evaluation.
SteampunkApproach for maintaining data quality and integrity across ETL pipelines.
SteampunkHow to tell whether a model is overfitting using train and validation performance.
SteampunkFramework for deciding if a model is ready for deployment using discrimination, calibration, threshold choice, and business impact.
SteampunkDesign an enterprise RAG pipeline for internal policy QA with embeddings, retrieval, citations, ACL filtering, and low-latency grounded generation.
SteampunkDesign a vector database-backed retrieval system for grounded LLM answers.
SteampunkA framework for prioritizing AI product features based on user value, feasibility, evaluation quality, and trade-offs.
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