Automated credential processing system

A system, comprising:

• one or more processors;
• and
• memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:
• receive a set of credentials associated with a user, wherein the set of credentials identifies a set of characteristics associated with the user;
• apply a category identification model to the set of credentials to generate a requisition category associated with the user, wherein the requisition category identifies a domain for the set of credentials, and wherein the category identification model is trained using previously processed sets of credentials and their respective requisition categories;
• apply a skill recognition model to the requisition category and the set of credentials after the category identification model generates the requisition category, wherein the skill recognition model generates a plurality of candidate tags associated with the domain identified by the requisition category, wherein the plurality of candidate tags identify skills associated with the set of characteristics, and wherein the skill recognition model is trained using the previously processed sets of credentials and their respective tags;
• remove a set of candidate tags from the plurality of candidate tags after the skill recognition model generates the plurality of candidate tags, wherein the set of candidate tags include personal identifiable information associated with the user, and wherein the set of candidate tags are removed to generate one or more anonymized tags for the set of credentials;
• identify one or more open requisitions using the one or more anonymized tags;
• rank the one or more open requisitions according to confidence scores associated with the one or more anonymized tags;
• receive feedback associated with a third-party system, wherein the feedback includes an indication of whether the user qualifies for the one or more open requisitions;
• update the category identification model and the skill recognition model using the one or more open requisitions and the feedback;
• and
• update the skill recognition model using the one or more anonymized tags, wherein updating the skill recognition model reduces bias associated with determining whether the user qualifies for the one or more open requisitions.

A non-transitory, computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:

• receive a set of credentials associated with a user, wherein the set of credentials identifies a set of characteristics associated with the user;
• apply a category identification model to the set of credentials to generate a requisition category associated with the user, wherein the requisition category identifies a domain for the set of credentials, and wherein the category identification model is trained using previously processed sets of credentials and their respective requisition categories;
• apply a skill recognition model to the requisition category and the set of credentials after the category identification model generates the requisition category, wherein the skill recognition model generates a plurality of candidate tags associated with the domain identified by the requisition category, wherein the plurality of candidate tags identify skills associated with the set of characteristics, and wherein the skill recognition model is trained using the previously processed sets of credentials and their respective tags;
• remove a set of candidate tags from the plurality of candidate tags after the skill recognition model generates the plurality of candidate tags, wherein the set of candidate tags include personal identifiable information associated with the user, and wherein the set of candidate tags are removed to generate one or more anonymized tags for the set of credentials;
• identify one or more open requisitions using the one or more anonymized tags;
• rank the one or more open requisitions according to confidence scores associated with the one or more anonymized tags;
• receive feedback associated with a third-party system, wherein the feedback includes an indication of whether the user qualifies for the one or more open requisitions;
• update the category identification model and the skill recognition model using the one or more open requisitions and the feedback;
• and
• update the skill recognition model using the one or more anonymized tags, wherein updating the skill recognition model reduces bias associated with determining whether the user qualifies for the one or more open requisitions.