Research On Accurate Portrait Of Talent Needs

With the advent of the big data era,artificial intelligence technology has brought profound impacts and changes to various industries.How to improve the efficiency and quality of talent recruitment through artificial intelligence technology has become a hot topic of concern in human resources.Nowadays,the domestic financial technology industry is developing rapidly,and the industrial internet is in the ascendant.The demand for talent,especially technical support engineers,in the financial technology industry is particularly urgent,which undoubtedly puts enormous pressure on the work of recruitment departments.Based on this,this article intends to use big data technology to collect and analyze the resumes of technical support engineers and a series of data generated during the recruitment process,conduct talent portrait research,and select several classification algorithms to verify their effectiveness.Strictly speaking,reconstructing multidimensional feature vectors such as job seekers’ resumes,job information on the internet,and evaluation data generated during the recruitment process is a talent portrait.From the perspective of resumes,structured data usually includes residence,date of birth,gender,etc.,and unstructured data usually includes learning background,internship experience,full-time work experience,etc.Such a large amount of data will produce many problems and challenges in the construction and verification of talent profiles.This article will use the professional knowledge gained during my master’s studies,such as rule extraction and virtual variable processing,to construct a talent profile and conduct validation.The idea behind verifying talent profiles in this article is to use classification algorithms to predict whether candidates who meet the talent profile can pass the resume screening stage and subsequent written interview stages,and to calculate accuracy.The results show that job seekers with more full-time work experience,accounting or computer related learning backgrounds in the financial technology industry have a higher probability of passing the screening of resumes.Finally,based on the real social recruitment data accumulated by a financial technology company in 2022,this article achieves the construction and effectiveness testing of talent profiles for technical support engineers.The research has preliminarily confirmed the effectiveness of the talent portrait in the article and provided targeted suggestions for talent recruitment in the financial technology industry and even the entire human resources industry.