1.9 KiB
AugmentX – Job Market Intelligence Platform
A Python-based job market intelligence platform designed to collect verified job postings directly from official company career pages and ATS platforms, transform raw postings into structured datasets, and generate actionable insights into hiring demand, role distribution, and skill trends.
Project Principles & Architecture
- Primary Data Sources: Official company career pages and Applicant Tracking Systems (ATS).
- Secondary Discovery Sources: Job discovery platforms are used exclusively to identify and locate official company career pages, not to scrape job postings.
- Core Technology Stack: Python, Requests/HTTP clients, HTML/JSON parsing, SQLite/PostgreSQL, and Pandas.
- Data Integrity: Source verification, structured ingestion, validation, and deduplication throughout the pipeline.
Project Roadmap
Phase 1: Job Source Intelligence & Crawl Prioritization
Build a structured source registry by identifying target companies, discovering official career pages and ATS platforms, validating accessible endpoints, and ranking sources based on job availability, data accessibility, and crawling feasibility.
Phase 2: Job Data Collection & Pipeline Automation
Develop modular crawlers, automate job-posting extraction, capture raw records, and establish a centralized database ingestion workflow.
Phase 3: Job Data Cleaning & Deduplication
Standardize job titles, company names, locations, and descriptions while implementing schema validation, entity normalization, and duplicate detection.
Phase 4: Search Interface & Market Exploration
Develop a searchable job discovery interface with role-based filtering, location-based exploration, and initial market analytics.
Phase 5: Labor Market Demand & Skills Intelligence
Extract and categorize skills using NLP/LLM techniques, analyze hiring demand across roles and technologies, and identify emerging skill trends and market patterns.