11. A system comprising: at least one data store configured to maintain profiles of all members, an evolving collection of unstructured data of each of the members, an evolving collection of historical data, and a rank model; and at least one server computer that together is configured to: receive from a first end device a request submitted by a first member of all members, wherein the first member is associated with a first type of member; receive from a plurality of second end devices a plurality of responses submitted by a subset of the members regarding the request, wherein each within the subset of members is associated with a second type of member that is different from the first type of member; in response to receiving the plurality of responses, access the at least one data store to retrieve the unstructured data that is specific to the first member and to retrieve the profiles associated with the subset of members who submitted the plurality of responses; dynamically determine, based on the unstructured data that is specific to the first member, a set of parameters that is only pertinent to the first member and is to be used by the rank model; for each in subset of members, determine, based on the rank model using the set of parameters that is only pertinent to the first member and based on the profile for a corresponding member, a rank score comprising a set of factor scores; and present an ordered listing of the members in the subset of members according to the rank scores; implement a mapping engine configured to: access the at least one data store to retrieve the historical data; and for each in the subset of members, compare the set of factor scores associated with the corresponding member to past sets of factor scores that are part of the historical data to determine, based on associated data that are part of the historical data and that are regarding whether respective service providers for the past set of factor scores had been awarded jobs, a percentage of likelihood of being selected for having the set of factor scores and to, thereby, map the corresponding member to one of at least two levels based on the determined percentage of likelihood of being selected, wherein each of the at least two levels are distinguished in the ordered listing; and receive from the first end device a selection, wherein information regarding the selection becomes part of the evolving collection of historical data.
11. A system comprising: at least one data store configured to maintain profiles of all members, an evolving collection of unstructured data of each of the members, an evolving collection of historical data, and a rank model; and at least one server computer that together is configured to: receive from a first end device a request submitted by a first member of all members, wherein the first member is associated with a first type of member; receive from a plurality of second end devices a plurality of responses submitted by a subset of the members regarding the request, wherein each within the subset of members is associated with a second type of member that is different from the first type of member; in response to receiving the plurality of responses, access the at least one data store to retrieve the unstructured data that is specific to the first member and to retrieve the profiles associated with the subset of members who submitted the plurality of responses; dynamically determine, based on the unstructured data that is specific to the first member, a set of parameters that is only pertinent to the first member and is to be used by the rank model; for each in subset of members, determine, based on the rank model using the set of parameters that is only pertinent to the first member and based on the profile for a corresponding member, a rank score comprising a set of factor scores; and present an ordered listing of the members in the subset of members according to the rank scores; implement a mapping engine configured to: access the at least one data store to retrieve the historical data; and for each in the subset of members, compare the set of factor scores associated with the corresponding member to past sets of factor scores that are part of the historical data to determine, based on associated data that are part of the historical data and that are regarding whether respective service providers for the past set of factor scores had been awarded jobs, a percentage of likelihood of being selected for having the set of factor scores and to, thereby, map the corresponding member to one of at least two levels based on the determined percentage of likelihood of being selected, wherein each of the at least two levels are distinguished in the ordered listing; and receive from the first end device a selection, wherein information regarding the selection becomes part of the evolving collection of historical data. 12. The system of claim 11 , wherein the at least one data store maintains a machine learning model configured to continuously learn from the unstructured data that is specific to the first member to determine data points that are relevant to the first member.