{"blocks": [{"key": "8f926899", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "789ce30e", "text": "Reviewing a predictive-analytics project end-to-end, from feature engineering to model evaluation and iteration.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "82e83fe1", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "7e46f17a", "text": "Describe a project where you used statistical or machine-learning techniques. What features did you engineer and what was the final output? In hindsight, what would you do differently to improve the model’s performance and business impact?", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "bd0e333e", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "87754178", "text": "Cover data sourcing, feature selection, algorithm choice, evaluation metrics, error analysis, and next-step improvements.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}