22. A computing system comprising: a data storage device; and a processing device, coupled to the data storage device, to execute a digital interviewing platform comprising a model-driven candidate-sorting tool, wherein the model-driven candidate-sorting tool is to: select 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; for the plurality of interviewing candidates, analyze the candidate data for the respective interviewing candidate to identify a plurality of digital interviewing cues; and apply the plurality of 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; sort a list of the plurality of interviewing candidates based on the predicted achievement indices from applying the plurality of digital interviewing cues to the prediction model; and present the sorted list of the plurality of interviewing candidates to a reviewer in a user interface of the digital interviewing platform.
22. A computing system comprising: a data storage device; and a processing device, coupled to the data storage device, to execute a digital interviewing platform comprising a model-driven candidate-sorting tool, wherein the model-driven candidate-sorting tool is to: select 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; for the plurality of interviewing candidates, analyze the candidate data for the respective interviewing candidate to identify a plurality of digital interviewing cues; and apply the plurality of 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; sort a list of the plurality of interviewing candidates based on the predicted achievement indices from applying the plurality of digital interviewing cues to the prediction model; and present the sorted list of the plurality of interviewing candidates to a reviewer in a user interface of the digital interviewing platform. 25. The computing system of claim 22 , wherein the digital interview data comprises audio data, wherein the model-driven candidate-sorting tool is further to: identify utterances in the audio data of a digital interview by the respective candidate, wherein the utterances each comprise a group of one or more words spoken by a candidate in the digital interview; and generate the audio cues of the digital interview based on the identified utterances.