SYSTEM, METHOD, AND COMPUTER PROGRAM FOR MANAGING TALENT EVENTS

1 . A computing system comprising one or more computers for managing talent events for an employer organization, the one or more computers comprising:

an interface device; and

a processing device, communicatively connected to the interface device to execute one or more workflows, to:

identify, based on a ranking of event participants to a talent event, target participants from the event participants, and transmit a request for information to each of the target participants;

responsive to receiving a first document submitted by at least one of the target participants, generate, based on the first document, a corresponding first enriched talent profile associated with the at least one target participant;

implement a machine learning module that is trained based on historical recruiting data relating to at least one of the talent event or an organization to which the at least one target participant belongs;

for a calibrated position profile, execute the trained machine learning module using the first enriched talent profiles and the calibrated position profile as inputs to calculate a match score associated with each of first enriched talent profiles; and

determine, based on calculated match scores, one or more target participants invited to meet at the talent event.

2 . The computing system of claim 1 , wherein the processing device is further to:

receive historical recruit data of past talent events and hire decisions, wherein the historical recruiting data comprise at least one of conversion rates from a number of resumes received to one of interviewed or offer made, offer accept rates with respect to one of event venues or schools attended by the potential participants, offer decline rates with respect to the event venues or the schools attended by the event participants, or pending offers with respect to the event venues or the schools attended by the event participants; and

present, on a graphical user interface of the interface device, the historical recruiting data.

3 . The computing system of claim 1 , wherein the processing device is further to:

implement a second machine learning module that is trained by adjusting at least one parameter of the second machine learning module based on information of past event participants to the talent event and the historical recruiting data, the information of past event participants to the talent event including at least one of courses taken, academic performance, projects accomplished, jobs held, or awards received by past event participants to the talent event;

identify information of the event participants to the talent event; and

execute the second machine learning module using the information of the event participants as inputs to calculate the ranking of event participants to the talent event.

4 . The computing system of claim 1 , wherein the first document comprises a resume submitted by the at least one of the target participants, and wherein the enrich talent profile comprises the resume, and at least one of:

first data items relating to at least one peer of the at least one target participant, and wherein the at least one peer is a past event participant of the talent event,

second data items relating to skills, companies, roles, schools, and fields of study similar to the at least one target participant's skills, companies, roles, schools, and fields of study,

third data items relating to at least one of a personality or a talent assessment for the at least one target participant based on the resume of the at least one target participant, or

a predicted data item comprising at least one of a future role, a future company, a future school, or a future field of study for the at least one target participant.

5 . The computing system of claim 1 , wherein the calculated match score represents a probability for a target participant to be interviewed or hired by the recruiting organization with respect to a particular position.

6 . The computing system of claim 1 , wherein the processing device is further to:

generate and transmit a customized invitation to each of the one or more target participants, wherein the customized invitation comprises at least one of a position description, the historical recruiting data relating to at least one of the talent event or the organization to which the corresponding target participant belongs to, a list of credentials possessed by the corresponding target participant that match one or more requirements in the position description, or information of a list of personnel who is currently associated with the recruiting organization.

7 . The computing system of claim 1 , wherein the processing device is further to generate a second graphical user interface to a recruiter, wherein the second graphical user interface comprises the potential participants and the target participants.

8 . The computing system of claim 7 , wherein responsive to selecting a third target participant in the second graphical user interface, the processing device is further to present drill-down views relating to the selected third target participant comprising at least one of:

a summary view of information associated with the third target participant;

a status view indicating a meeting schedule and status of the third target participant at the talent event;

a list of questions for the recruiter to direct at the third target participant, wherein the list of questions are customized for the third target participant; or

an evaluation view for the recruiter to evaluate the third target participant after meeting the third target participant.

9 . The computing system of claim 1 , wherein the processing device is further to generate a third graphical user interface to present a communication page for inviting a fourth target participant to participate in a future event based on a corresponding match score associated with the fourth target participant.

10 . A method for managing talent events for a recruiting organization, the method comprising:

identifying, by a processing device based on a ranking of event participants to a talent event, target participants from the event participants, and transmit a request for information to each of the target participants;

responsive to receiving a first document submitted by at least one of the target participants, generating, based on the first document, a corresponding first enriched talent profile associated with the at least one target participant;

implementing a machine learning module that is trained based on historical recruiting data relating to at least one of the talent event or an organization to which the at least one target participant belongs;

for a calibrated position profile, executing the trained machine learning module using the first enriched talent profiles and the calibrated position profile as inputs to calculate a match score associated with each of first enriched talent profiles; and

determining, based on calculated match scores, one or more target participants invited to meet at the talent event.

11 . The method of claim 10 , further comprising:

receiving historical recruit data of past talent events and hire decisions, wherein the historical recruiting data comprise at least one of conversion rates from a number of resumes received to one of interviewed or offer made, offer accept rates with respect to one of event venues or schools attended by the potential participants, offer decline rates with respect to the event venues or the schools attended by the event participants, or pending offers with respect to the event venues or the schools attended by the event participants; and

presenting, on a graphical user interface, the historical recruiting data.

12 . The method of claim 10 , further comprising:

implementing a second machine learning module that is trained by adjusting at least one parameter of the second machine learning module based on information of past event participants to the talent event and the historical recruiting data, the information of past event participants to the talent event including at least one of courses taken, academic performance, projects accomplished, jobs held, or awards received by past event participants to the talent event;

identifying information of the event participants to the talent event; and

executing the second machine learning module using the information of the event participants as inputs to calculate the ranking of event participants to the talent event.

13 . The method of claim 10 , wherein the first document comprises a resume submitted by the at least one of the target participants, and wherein the enrich talent profile comprises the resume, and at least one of:

first data items relating to at least one peer of the at least one target participant, and wherein the at least one peer is a past event participant of the talent event,

second data items relating to skills, companies, roles, schools, and fields of study similar to the at least one target participant's skills, companies, roles, schools, and fields of study,

third data items relating to at least one of a personality or a talent assessment for the at least one target participant based on the resume of the at least one target participant, or

a predicted data item comprising at least one of a future role, a future company, a future school, or a future field of study for the at least one target participant.

14 . The method of claim 10 , wherein the calculated match score represents a probability for a target participant to be interviewed or hired by the recruiting organization with respect to a particular position.

15 . The method of claim 10 , further comprising:

generating and transmitting a customized invitation to each of the one or more target participants, wherein the customized invitation comprises at least one of a position description, the historical recruiting data relating to at least one of the talent event or the organization to which the corresponding target participant belongs to, a list of credentials possessed by the corresponding target participant that match one or more requirements in the position description, or information of a list of personnel who is currently associated with the recruiting organization.

16 . The method of claim 10 , further comprising generating a second graphical user interface to a recruiter, wherein the second graphical user interface comprises the potential participants and the target participants.

17 . The method of claim 16 , further comprising:

responsive to selecting a third target participant in the second graphical user interface, presenting drill-down views relating to the selected third target participant comprising at least one of:

a summary view of information associated with the third target participant;

a status view indicating a meeting schedule and status of the third target participant at the talent event;

a list of questions for the recruiter to direct at the third target participant, wherein the list of questions are customized for the third target participant; or

an evaluation view for the recruiter to evaluate the third target participant after meeting the third target participant.

18 . The method of claim 10 , further comprising generating a third graphical user interface to present a communication page for inviting a fourth target participant to participate in a future event based on a corresponding match score associated with the fourth target participant.

19 . A machine-readable non-transitory storage media encoded with instructions that, when executed by one or more computers, cause the one or more computer to implement a system for managing talent events for a recruiting organization, to:

identify, based on a ranking of event participants to a talent event, target participants from the event participants, and transmit a request for information to each of the target participants;

responsive to receiving a first document submitted by at least one of the target participants, generate, based on the first document, a corresponding first enriched talent profile associated with the at least one target participant;

implement a machine learning module that is trained based on historical recruiting data relating to at least one of the talent event or an organization to which the at least one target participant belongs;

for a calibrated position profile, execute the trained machine learning module using the first enriched talent profiles and the calibrated position profile as inputs to calculate a match score associated with each of first enriched talent profiles; and

determine, based on calculated match scores, one or more target participants invited to meet at the talent event.