What is Resume Parsing?

Basically, it is a technology used to read information from a resume or a CV.

Current resume parsers use numerous AI neural networks and data science models to extract structured data. Most common information being extracted are about a candidate’s personal details, work experience, education and skills.

The technology is also used to automatically create a detailed candidate profile (Imagine uploading a resume to LinkedIn and automatically creating a profile, or editing a LinkedIn pdf into a great looking CV).

The extracted data can be used for a range of applications from simply populating a candidate in a CRM, to candidate screening, to full database search. These tools can be integrated into a software or platform, to provide near real time automation.

Many HR Professionals and ATS use CV and Resume Parsing tools to automate the storage, import and analysis of data and text on CVs and resumes.

The most common format of a CV or resume that recruiters receive is Word or PDF. Even though these documents are easy to read and understand to us, computer interpretation is more difficult.

Resume parsing benefits and use case

It is used in almost every Applicant Tracking Systems (ATS), internal recruitment teams, HR technology platforms, niche staffing services, and job boards – ranging from tiny start-ups all the way through to large enterprises and government agencies.

1. ‍Creating complete candidate profiles : Automatically populate candidate profiles, without needing to manually enter information
2. Sorting Candidates  : By years experience, skills, work type, education, and more. Extracted data can be used to create job matching engine and logics.
3. Creating a database : An organisation can have hundreds of thousands of resumes in their database. Resume parsing can be used to create a structured candidate information, to transform your resume database into an easily searchable and high-value asset

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