1. A system for prioritizing a list of job candidates for a job opening with a firm, the system comprising: at least one computer system comprising at least one processor and at least one memory unit that is in communication with the at least one processor, wherein the at least one processor is programmed to: use a Random Forest Algorithm to generate a quantity T decision trees, where T is greater than or equal to 2, and the T decision trees are trained based on a training data set of historical candidates classified into hired or unhired classes, wherein each decision tree of the T decision trees is generated by selecting historical candidates in the training dataset randomly with replacement to train the decision tree; and for each of the job candidates, determine a classification of the job candidate for each of the T decision trees; compute a hiring probability for each job candidate based on a ratio of (i) a total of number of times the job candidate was classified as hired to (ii) T; and rank the job candidates by hiring probability to generate a prioritized list of the job candidates.