AI Resume Volume Processing

Filtering Resumes and Identifying the Best Candidate Match

Resume screening is the first step in the recruitment and staffing process. It involves the identification of relevant resumes or CVs for a certain job role based on their qualifications and experience. However, the traditional method of manually screening a prodigious volume of resumes is a time-consuming and laborious task.

One estimate suggests that it takes around 23 hours for an average human resource person to screen resumes and classify the right profiles.

Artificial intelligence is the potential future of resume screening powered by high computational powers and machine learning algorithms. The automated systems can be well integrated with the Application Tracking Systems (ATS) to screen high volumes of resumes efficiently.

The natural language processing (NLP) engines underlying AI can streamline the resume screening process in the following manner-

a) The NLP algorithm uses a pre-defined terminology of keywords such as “AI developer”, “Keras” or “TensorFlow” to parse the resumes.

b) The system then ranks the resumes based on the occurrence and frequency of the above-mentioned keywords. We can use the data visualization library, Matplotlib to analyze and rank keywords by category.

c) The end result is an automated system that can analyze complex resumes and categorize relevant candidates based on specified profile keywords. The integration of AI with ATS accelerates the recruitment process and performance without compromising with the quality of hire.