The image shows the match score computation. Assume the job profile requires competencies in Artificial Intelligence and Data Science. The profile matching subject area runs a trained similarity algorithm against the worker's talent profile, assigning a matching score for each competency. If the worker's talent profile includes Artificial Intelligence, a value of 1 is assigned. If the job requires Data Science but the worker has only Analytical Thinking, a similarity value of 0.3 is assigned (this is based on vector representation of cosine similarity of embeddings). Similarity scores are given for all attributes, and the matching score is the average of these items; in this case, it would be (1 + 0.3) / 2 = 0.65. We also provide upskilling requirement for each of the attributes that can help a worker become eligible for the job profile. Attributes with a score less than 0.5 are shown as upskilling requirements for the candidate. The matching occurs against all the model job profiles that are setup and all the worker’s having active talent profiles. Match Score ranges from -1 to 1 where:

• -1 indicates exactly opposite characteristics to that required by the job.
• 1 indicates exactly similar characteristics to that required by the job.
• 0 indicates that the characteristics of person profile are neither opposite nor similar to that required by the job; they are unrelated.