Automated Job Portal Optimization for Enhanced Matching and Scalability

Recruitment & Talent Acquisition

Business services

Identified Challenges in Job Listing Management and Application Processing

The client’s job portal faced issues with inaccurate job categorization, leading to poor job matching, and a manual, resource-intensive application process limiting scalability. These issues hinder staff productivity and user experience, especially as the platform grows.

About the Client

A growing startup operating a job portal platform tasked with improving job categorization accuracy and streamlining application processes to scale efficiently.

Key Goals for Improving Job Portal Functionality and Efficiency

Enhance the accuracy of job listing categorization to improve job seeker-match quality.
Automate the application process through form autofill and keyword extraction to reduce processing time and resource utilization.
Implement scalable and robust infrastructure capable of supporting growth and increased data volume.
Establish a technological foundation with clear automation workflows and data relationships.

Core System Functionalities for Automated Job Matching Platform

Web scraping tool to extract relevant keywords from job listings for accurate categorization.
Automated autofill capabilities for application forms based on extracted keywords and data relationships.
Database architecture to store and manage relationships between job offers, candidates, and categorization data.
Recommendation engine to improve job-candidate matching accuracy.

Preferred Technologies and Architectural Approach

Python, Selenium for web scraping and automation

FastAPI for backend API development

Graph database (e.g., Neo4j) for relationship management

Relational database (e.g., PostgreSQL) for structured data storage

Machine learning libraries (e.g., sklearn) for recommendation engine

Essential External System Integrations

Job listing platforms for data ingestion
Applicant tracking systems for data synchronization
External APIs for keyword extraction and NLP processing

Critical Non-Functional System Requirements

System scalability to support rapid growth within 12 weeks of deployment
High performance with real-time data processing and response times under 1 second
Robust security measures to protect user data and comply with data privacy standards
High system availability with 99.9% uptime

Projected Business Benefits from Automation and Optimization

The implemented solution aims to dramatically improve job categorization accuracy, leading to better matching efficiency. It expects to reduce manual processing time by over 50%, streamline application workflows, and support scalable growth, ultimately enhancing user satisfaction and operational efficiency.