Candidate Clustering – Moyyn

Cluster the candidate data via machine learning techniques such as K-Means clustering, Hierarchical clustering, and Natural Language Processing (NLP)

About the project:

This project aims to implement CV based candidate clustering using data science methods for candidates applying through Moyyn. By analyzing the structured and unstructured data in CVs, the goal is to segment candidates into meaningful groups based on various factors such as skills, work experience, education, industry, and other relevant attributes. The segmentation will help Moyyn categorize candidates for better job matching, personalized recommendations, and efficient recruitment processes. Using machine learning techniques such as K-Means clustering, Hierarchical clustering, and Natural Language Processing (NLP), the CV segmentation will provide a robust and scalable solution for managing large candidate pools.

About the company:

Moyyn is a recruitment tech company that offers AI-powered solutions to streamline the hiring process. Their platform helps businesses and recruiters automate various tasks in recruitment, such as candidate sourcing, screening, and engagement, using artificial intelligence and machine learning. Moyyn’s technology enables faster, more efficient hiring by matching candidates with job openings based on their skills, experience, and qualifications. Additionally, it provides tools to enhance candidate experience and reduce the manual workload for recruiters. They often cater to startups, small and medium-sized enterprises (SMEs), and large companies looking to improve their recruitment workflows and discover the best talent more efficiently.

Tools you will learn and work with:
– Python
– Microsoft Excel
– ChatGPT
– NLP Techniques, K-means, Hierarchial clustering

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