A Data-Driven Framework for Personalized Career Guidance

Author(s)	Ms. Megha
Country	India
Abstract	In today’s fast-growing and highly competitive job market, candidates often struggle to choose the right career path and align their skills with industry demands. Traditional career counseling methods are limited, time-consuming, and often fail to provide personalized guidance. At the same time, companies increasingly use Applicant Tracking Systems (ATS) and AI-based recruitment tools, making it essential for job seekers to optimize their resumes and match their competencies with evolving job requirements. Advancements in artificial intelligence, natural language processing, and machine learning have opened new possibilities for improving career guidance. These technologies can analyze resumes, identify missing skills, and match candidates to appropriate job roles more accurately than conventional methods. This research aims to develop a data-driven, AI-powered framework that supports individuals—especially early-career professionals, job seekers, and those seeking career transitions—in making informed and personalized career decisions.
Keywords	Career advice, AI resume analysis, skill gap analysis, job matching, career roadmap customization, personal development, ATS compatibility
Field	Engineering
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-01-07
DOI	https://doi.org/10.36948/ijfmr.2026.v08i01.62911
Short DOI	https://doi.org/hbh55n

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International Journal For Multidisciplinary Research