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.

An analysis of abilities, skills and tech skills data from the O*NET database as well as classification of around 500 random LinkedIn job titles.

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This Python script scrapes up to 100 most recent Linkedin job postings of any job title and creates sentiment visualization in a form of a word cloud.

This repository presents an end-to-end analysis of LinkedIn's professional networking platform's Jobs section. The project aims to extract over 500 job details from LinkedIn's website and analyze it.

LinkedIn job postings analysis (over 15000 data) using Apache Spark, Plotly, and Streamlit. Mainly focused on open job count and monthly salary.

Scrapedin is a Python module designed to simplify the process of gathering job listings from LinkedIn and performing data analysis on the scraped data to develop an understanding for the required skills and more needed in the market in real-time!

Automated job search and analysis for LinkedIn & Xing with AI-powered filtering

LinkedIn Job Scraper with a Text-Based User Interface (TUI) is a command-line tool designed to simplify the extraction of job listings from LinkedIn. This project focuses on providing users with a command-line interface that allows them to extract job information and export the scraped data into a CSV file for further analysis.

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.

Jobs have been scraped from linkedin to perform a data analysis to optimize the CV and cover letter

Linkedin data science job postings analysis using natural language processing techniques and prediction on candidate's education level

Our winner project of the Microsoft Fabric and AI Learning Hackathon: Sweden's Linkedin jobs Analysis

A data pipeline to collect LinkedIn's job posting data for analysis and study job market better using techniques like NLP.

LinkedIn Scraper is a powerful job scraping tool designed for job seekers and recruiters. With just one click, extract job listings from LinkedIn, including job title, description, apply link, published date, recruiter name, and profile link. Easily export the collected data to a CSV file for seamless analysis and tracking.

AI-powered LinkedIn profile optimizer using job market data analysis. Generate optimized titles, about sections, and experience entries with Claude Code.

AI-powered resume-to-job matching system with LinkedIn integration. Upload resume + LinkedIn URL → get instant AI match analysis with scores, missing skills & recommendations. Multi-LLM support (GPT-4, Claude, Gemini). Built with FastAPI, PostgreSQL+pgvector, Redis, Docker.

This Python project involves scraping job offers from a website (LinkedIn) and then visualizing the results. This project likely involves the use of web scraping techniques to extract job offer data from LinkedIn, followed by the use of data analysis and visualization tools to present the results in a clear and meaningful way.

Scraping LinkedIn Data-Related job postings and Analysing job market trends in Indonesia.

Linkedin trending jobs analysis BI project

Detect ghost jobs on LinkedIn with real-time analysis and user-friendly interfaces for both job seekers and recruiters.

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

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.

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.

📊 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.

LinkedIn Job Market Analytics – Power BI Dashboard

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.

data analysis & classification from data scraped from Linkedin

Scrape Data Analysis Jobs from Naukri.com and Linkedin.com

This project analyzes a dataset of entry-level data analyst job postings in Europe collected from LinkedIn. The analysis identifies top hiring companies, countries with the most opportunities, and the most common job titles for data analysts. The results are visualized using bar charts for easy interpretation.