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Predicting customer renewal probability and optimizing sales agents time spent on each customer. This submission ranked top 4 percent in McKinsey Data Scientist hiring hackathon. LGBM, Scipy.

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Predicting insurance company customer renewal probability and optimizing sales agents time spent on each customer.

Solution for McKinsey Data Scientist Hiring Hackathon. https://datahack.analyticsvidhya.com/contest/mckinsey-analytics-online-hackathon-4/

Techniques used:

Light Gradient Boosting Model (LGBM) to build a high accuracy tree model.

RandomizedSearchCV (Scikit learn) to train LGBM with different combinations of hyperparameters using CrossValidation.

Scipy to find input value that maximizes outoput for a function.

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Predicting customer renewal probability and optimizing sales agents time spent on each customer. This submission ranked top 4 percent in McKinsey Data Scientist hiring hackathon. LGBM, Scipy.

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