Job segmentation and clustering – Moyyn

Segment the job data using Machine Learning techniques

About the project:

This project aims to implement job segmentation and clustering using Machine Learning (ML) methods for Moyyn. The primary goal is to categorize and cluster jobs posted on Moyyn’s platform based on various attributes such as required skills, industry, location, salary range, and job descriptions. This segmentation will help Moyyn and its clients better understand the types of jobs being offered, optimize the job matching process for candidates, and streamline recruitment strategies for companies. Using ML techniques such as K-Means Clustering, Hierarchical Clustering, and Natural Language Processing (NLP), the project will segment job postings into distinct categories that align with the skills and preferences of candidates.

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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