Data analysis of the Brazilian data job market through LinkedIn scraping. Extracts and standardizes job titles and skills, with insights visualized in Power BI dashboards.

AI-powered job matching system that automatically fetches jobs from LinkedIn & SEEK, matches them against your resume using Google's Gemini API, and enriches results with Glassdoor company insights.

Maargha AI is a multi-agent platform that provides personalized career guidance, LinkedIn optimization, job matching, emotional support, and daily insights. A master agent orchestrates all features, allowing users to access everything through simple natural conversations.

The latest and most advanced Google Job Scraper. Our Indeed, Linkedin, and Google Jobs Scraper rolled into one. This scraper extracts real-time job postings at scale from any active Google Jobs search results from all over the world. A new research tool built for recruitment, insights and HR.

The latest and most advanced LinkedIn Job Scraper. Our LinkedIn Jobs Scraper extracts real-time job postings at scale from all over the world. A new research tool built for recruitment, insights and HR.

This project aims to implement a detector of similar job descriptions using big data analysis techniques on the LinkedIn Jobs & Skills dataset. By leveraging PySpark, we will uncover insights and patterns in the job summary data to help employers and job seekers better understand the job market.

In order to help students and job seekers in their journey of job hunting, from our experience we got the idea to start the project after the successful result of the first prototype that we build for personal use (massive job hunting). The app extract the data of given job (link of Linkedin or any job search platform) and use it to build a short insight that focus on the important key words, required Skills, level of education and information about the company. The extracted job data and the user data (Resume, Profile) will be used as input of the processing box (the sniper agency), It has Intelligente agent that use many tools and technique to produce results for example : The NLP text generator (we call it the philosopher) that produce a perfect motivation letter based on the input and some other predefined data. the second agent "The advisor" : it help the user to know the job skill set that he needs to master before applying to the job he is interested in, even we suggest online courses based on users rating, in general we use prediction models in this part.

Chrome extension for LinkedIn job postings that reveals the exact number of applicants by intercepting JSON data from the frontend. Add transparency to job offers, track application counts in real time, and enhance your LinkedIn job search with clear insights.

End-to-end job market analysis using real LinkedIn job postings scraped via Python. Includes web scraping, skill extraction, EDA, Excel-based validation, and a Canva-designed dashboard showcasing hiring trends, in-demand skills, and location-wise insights.

LinkedIn Premium shows applicant counts, but scrolling can be tedious. This extension displays the count for the current job in the top right corner, with a customizable red limit.

Insights on skills and salaries using real data (scraped from Linkedin) - https://rafabelokurows.github.io/data-analyst-job-skills/

🌐 Scrape fresh LinkedIn job listings effortlessly, delivering structured data for analysis, recruitment, and salary insights without an account or cookies.

An advanced data analytics pipeline that provides deep insights into LinkedIn's job market trends. Utilizing technologies like Python, Apache Kafka, Spark, and AWS, it offers real-time and batch analysis of job listings, skill demands, and salary predictions, making it a vital tool for job seekers and recruiters.

🧑💼 Scrape and aggregate LinkedIn job listings effortlessly, providing real-time data and structured insights to enhance your job portal or research needs.

Insights and data visualization from linkedin data job postings. Uses pandas and matplotlib libraries!

An NLP-powered job market intelligence app that clusters LinkedIn job postings into occupational segments and surfaces salary benchmarks, similar roles, and market structure insights.

A comprehensive job market analysis platform that scrapes job postings from major job sites (LinkedIn, Indeed, Glassdoor) and provides real-time insights into the Kenyan job market including salary trends, skill demand, remote work opportunities, and hiring patterns.

This project seeks to analyse the data analyst job listings found on LinkedIn. The aim of the jobs analysis is to find hidden insights about data analyst jobs such as what skills are most in demand by employers.

A Flask-based Q&A app using Llama 3.2, built on scraped LinkedIn job data (Dhaka, Bangladesh) by Selenium. Users can query job-related insights powered by AI for quick, relevant answers.

📊 Exploratory Data Analysis (EDA) of LinkedIn job postings in India. Features insights on in-demand roles, experience levels, and hiring sectors using Python, Pandas, and Seaborn.

web scraping specialist leveraging Python (BeautifulSoup, Selenium) to extract job data from LinkedIn. Expertise in data processing and CSV conversion, with seamless email integration for automated delivery. Gain valuable insights efficiently.

Deep Dive into the 2023-2024 LinkedIn Job Market. This project features an intensive ETL pipeline (Python) for cleaning and structuring complex job data. Data is stored in MySQL and visualized with Power BI to extract insights on hiring trends, required skills, and salary benchmarks

The project analyzed LinkedIn's job market by ethically scraping data using Python (Selenium, Beautiful Soup) and cleaning it with Pandas. It identified job market trends through Power BI and DAX, with insights presented via an interactive dashboard. Collaboration with cross-functional teams ensured a thorough analysis.

An interactive dashboard providing deep insights into career opportunities for data-related roles, utilizing a comprehensive dataset sourced from LinkedIn. Features include analysis of experience levels, salaries, key skills, job locations, and industry trends, aiding job seekers and professionals in exploring and identifying optimal career paths.

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Analysis of a dataset containing information on 30,000+ job postings collected from LinkedIn.

Chrome Extension that displays real-time job post insights (applies, views, posted date) directly on LinkedIn job pages.

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Scraping LinkedIn job board and using GPT-4 to extract domain level insights

This project analyzes real LinkedIn job postings (2023–2024) to uncover insights about the modern job market.