Year: 2025
Type: article
Abstract: -The fast-paced changing job market creates serious challenges in talent attraction, requiring more effective and data-centric methods to automate the recruitment process. This paper introduces JobPathway, a full-fledged MERN stack application to maximize talent attraction using AI-driven resume parsing and job and profile reminder personalization. Utilizing sophisticated machine learning algorithms, JobPathway processes candidate profiles, identifies them with suitable job openings, and provides timely alerts in order to increase interactions and avoid lost opportunities. Further, the platform is envisioned to have quiz and interview planning functionalities so that recruiters and candidates can conduct the entire recruitment process in one integrated interface. This paper describes the system architecture, main components, and possible effect of JobPathway in improving recruitment efficiency and user experience. Key Words: Talent Acquisition, Artificial Intelligence (AI), Machine Learning (ML), Resume Parsing, Job Matching, Skill Recommendations, Predictive Analytics, Recruitment Systems, Role-Based Access Control, Job Seekers, Recruiters, Candidate Profiling, Automated Hiring, AI-powered Recruiting, Job Recommendation Systems, Behavioral Assessment, Interview Scheduling, Predictive Reminders, AI in HR, Recruitment Automation, AI-driven Talent Management, Node.js, Express, MongoDB, JWT, OAuth, Axios, Bcrypt, Frontend Development, MERN Stack, Backend Development, Web Development, Cloud Computing, REST APIs, Authentication, Authorization, Cloudinary, Responsive Design, Web Security.
DOI: 10.55041/ijsrem47414
Author: Chanchal Garg
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4410233641