A method, comprising: obtaining, by a device, a set of observations obtained from historical data including historical data identifying historical employee data, historical skill data, and/ or historical similarity scores; deriving, by the device, a feature set from the set of observations; pre-processing and/or performing dimensionality reduction, by the device, to reduce the feature set and/or combine features of the feature set to a minimum feature set; training, by the device, a similarity model on the minimum feature set; obtaining, by the device, skill data identifying skills of one or more employees; processing (115, 620, 730, 830), by the device, the skill data, with the similarity model, to determine similarity scores between the skills of the skill data, wherein the similarity model includes a cosine similarity on a weighted bipartite graph model; adding or removing (120, 630, 740, 840), by the device, one or more skills to or from the skill data for one or more predefined target skill profile categories, based on the similarity scores and to generate modified skill data; comparing (125, 640, 750, 850), by the device, the similarity scores and a predefined threshold to determine anchor skill data from the modified skill data and for each of the predefined target skill profile categories, wherein the anchor skill data includes skills from the modified skill data, with similarity scores that satisfy the predefined threshold; grouping (130, 650, 760, 860), by the device, the anchor skill data for corresponding pluralities of the predefined target skill profile categories, based on one or more predefined group categories and to generate groups of the anchor skill data; processing (135, 660, 770, 870), by the device, the groups of the anchor skill data and the similarity scores, with a clustering model, to generate clustered anchor skill data for each of the one or more predefined group categories, wherein the clustering model is trained with historical groups of anchor skill data and historical similarity scores associated with historical skill data and historical employee data for a plurality of employees, wherein the clustering model includes a Louvain clustering model; and performing (140, 670, 880), by the device, one or more actions based on the clustered anchor skill data, wherein performing the one or more actions comprises: retraining the similarity model based on the clustered anchor skill data; and retraining the clustering model based on the clustered anchor skill data. obtaining, by a device, a set of observations obtained from historical data including historical data identifying historical employee data, historical skill data, and/ or historical similarity scores; deriving, by the device, a feature set from the set of observations; pre-processing and/or performing dimensionality reduction, by the device, to reduce the feature set and/or combine features of the feature set to a minimum feature set; training, by the device, a similarity model on the minimum feature set; obtaining, by the device, skill data identifying skills of one or more employees; processing (115, 620, 730, 830), by the device, the skill data, with the similarity model, to determine similarity scores between the skills of the skill data, wherein the similarity model includes a cosine similarity on a weighted bipartite graph model; adding or removing (120, 630, 740, 840), by the device, one or more skills to or from the skill data for one or more predefined target skill profile categories, based on the similarity scores and to generate modified skill data; comparing (125, 640, 750, 850), by the device, the similarity scores and a predefined threshold to determine anchor skill data from the modified skill data and for each of the predefined target skill profile categories, wherein the anchor skill data includes skills from the modified skill data, with similarity scores that satisfy the predefined threshold; grouping (130, 650, 760, 860), by the device, the anchor skill data for corresponding pluralities of the predefined target skill profile categories, based on one or more predefined group categories and to generate groups of the anchor skill data; processing (135, 660, 770, 870), by the device, the groups of the anchor skill data and the similarity scores, with a clustering model, to generate clustered anchor skill data for each of the one or more predefined group categories, wherein the clustering model is trained with historical groups of anchor skill data and historical similarity scores associated with historical skill data and historical employee data for a plurality of employees, wherein the clustering model includes a Louvain clustering model; and performing (140, 670, 880), by the device, one or more actions based on the clustered anchor skill data, wherein performing the one or more actions comprises: retraining the similarity model based on the clustered anchor skill data; and retraining the clustering model based on the clustered anchor skill data. retraining the similarity model based on the clustered anchor skill data; and retraining the clustering model based on the clustered anchor skill data.