Predicting hiring priorities

A system, comprising:

• one or more processors;
• and
• memory storing instructions that, when executed by the one or more processors, cause the system to:
• determine hiring features characterizing hiring activity by an entity for a set of talent pools;
• apply a first machine learning model to the hiring features to produce a first set of scores representing future hiring growth by the entity for the set of talent pools;
• generate a first ranking of the set of talent pools by the first set of scores;
• and
• output at least a portion of the first ranking as a first prediction of the future hiring growth by the entity.

A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method, the method comprising:

• determining hiring features characterizing hiring activity by a company for a set of titles;
• applying a first machine learning model to the hiring features to produce a first set of scores representing future hiring volumes by the company for the set of titles;
• applying a second machine learning model to the hiring features to produce a second set of scores representing future hiring growth by the company for the set of titles;
• generating a first ranking of the set of titles by the first set of scores and a second ranking of the set of titles by the second set of scores;
• outputting at least a portion of the first ranking as a first prediction of the future hiring volumes by the company;
• and
• outputting at least a portion of the second ranking as a second prediction of the future hiring growth by the company.