12. A method comprising: selecting, by a model-driven candidate-sorting tool executing on a processing device, a data set of digital interview data for model-driven candidate sorting, wherein the data set comprises candidate data recorded for a plurality of interviewing candidates, wherein the candidate data comprises voice-to-text data; for the plurality of interviewing candidates, analyzing, by the model-driven candidate-sorting tool, the candidate data for the respective interviewing candidate to identify a plurality of digital interviewing cues, including audio cues, wherein analyzing the candidate data comprises generating, by an audio cue generator of the model-drive candidate sorting tool, the audio cues based on the voice-to-text data for the respective interviewing candidate; and applying the digital interviewing cues to a prediction model to predict an achievement index based on the plurality of digital interviewing cues identified for the respective interviewing candidate, wherein the applying the plurality of digital interviewing cues to the prediction model to predict the achievement index is performed without reviewer input at the model-driven candidate-sorting tool; sorting a list of the plurality of interviewing candidates based on the predicted achievement indices from the applying the plurality of digital interviewing cues to the prediction model; and presenting the sorted list of the plurality of interviewing candidates in a user interface to a reviewer.
12. A method comprising: selecting, by a model-driven candidate-sorting tool executing on a processing device, a data set of digital interview data for model-driven candidate sorting, wherein the data set comprises candidate data recorded for a plurality of interviewing candidates, wherein the candidate data comprises voice-to-text data; for the plurality of interviewing candidates, analyzing, by the model-driven candidate-sorting tool, the candidate data for the respective interviewing candidate to identify a plurality of digital interviewing cues, including audio cues, wherein analyzing the candidate data comprises generating, by an audio cue generator of the model-drive candidate sorting tool, the audio cues based on the voice-to-text data for the respective interviewing candidate; and applying the digital interviewing cues to a prediction model to predict an achievement index based on the plurality of digital interviewing cues identified for the respective interviewing candidate, wherein the applying the plurality of digital interviewing cues to the prediction model to predict the achievement index is performed without reviewer input at the model-driven candidate-sorting tool; sorting a list of the plurality of interviewing candidates based on the predicted achievement indices from the applying the plurality of digital interviewing cues to the prediction model; and presenting the sorted list of the plurality of interviewing candidates in a user interface to a reviewer. 15. The method of claim 12 , wherein the plurality of digital interviewing cues comprise at user interaction cues, wherein the candidate data comprises a log of user interactions, and wherein the analyzing the candidate data comprises generating the user interaction cues for the respective interviewing candidate based on the log of user interactions.