{"blocks": [{"key": "7c7fee6c", "text": "Scenario: LinkedIn Sales Solutions wants to automatically classify members who are likely sales professionals.", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "a5773738", "text": "Question 1: What features and data sources would you leverage to build the classifier?", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "c40158a9", "text": "Question 2: How would you label ground truth and address class imbalance?", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "bc194f22", "text": "Question 3: Which modeling approaches would you start with and why?", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "4bc92ce9", "text": "Question 4: How would you evaluate the model both offline and online?", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}