Identification of candidate that can be utilized as remote working resources using machine learning techniques

Abstract

" This research is on the idea of how ideal candidates for remote working can be assessed for stage one recruitment. It explores various ways of creating a single model to provide results for analysis via machine learning techniques. The global pandemic has caused the urgency of shift to such remote models and organisations have not had enough exposure in handling such change. Thus, this creates a reasonable demand for the recruitment behavior assessing model. The model considers various factors that affect behavioural patterns of employees in the IT sector such as personality, life-style, gender etc. and its results have been interpreted using the potential data analytic tool. Many theories were discussed to identify which data analytic tools and techniques would be most appropriate for the research along with the interpretation of such data. This study later interprets the data collected from respondents to identify a potential candidate in the IT sector. In the end, this research reflects the importance of a recruitment model for remote working using machine learning and the main objective of the study is to create such user-friendly model for use by IT organizations. "