Predictive Hiring Micro Systems for Data Analysts Through Soft Skills Assessment

The Human Resources sector faces a formidable challenge in identifying candidates who can seamlessly integrate into diverse organizational settings and contribute to overall success. The repercussions of suboptimal recruitment practices are profound, casting a shadow over an organization’s trajectory and development. Soft skills, encompassing personality traits and behaviors, are crucial attributes recruiters seek to ensure optimal performance and job success among candidates. This paper advocates for a groundbreaking predictive hiring model tailored specifically for the Data Analyst role within human resources. This innovative model is a strategic tool for recruiters, empowering them to discern and select the most suitable candidates while steering clear of detrimental recruitment decisions. The model’s execution hinges on leveraging a sophisticated machine learning algorithm, the Support Vector Machine algorithm, employing various functions to discern the most effective implementation. This research endeavors to revolutionize the hiring landscape, offering a reliable framework to elevate the precision and efficacy of candidate selection for organizations needing skilled Data Analysts.