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.

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.

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

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

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.

📊 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.

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.

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.

Selecting the right career is one of the most important decisions students have to make. With the increase in the number of career paths and opportunities, making this decision have become quite difficult. The purpose of this project is to do a job market analysis in Lebanon to provide information about different job trends in Lebanon up-to-date to Lebanese students, so they could form better career choices. Since many Lebanese students don’t know which major to choose and which job position is highly demanded in Lebanon, this project guides them in their career choice. The problem in Lebanon is that there’s no available data about the job market in Lebanon. Thus, I scrapped different websites to get information about job market trends in Lebanon and information about job professions as well. The design and methodology and methodology of this project is to scrape data about all job positions in Lebanon on LinkedIn, then clean and preprocess the data, turn it into a csv file then present it as visual graphs on a dashboard on Streamlit WebApp. Next, scrape data about job professions from O*net website to get information about different job professions. Then, clean and preprocess the data and present it as visual graphs on Streamlit WebApp. The major findings of this project were that the most demanded job position in Lebanon are manager and software engineer, the top hiring company is Toptal and Agoda, the city with the most job openings is Beirut. This project doesn’t only benefit Lebanese students and help them choose the right career for them, but also, it helps Lebanon’s economy. When worker’s skills and qualifications fit demanded jobs in the country then that increases productivity and boosts economic growth.

This repository contains a comprehensive analysis of jobs employment data for different industries and company. The primary focus is top assess the revisions in filled jobs figures by linkedin. Linkedin jobs data analysis and visualization using Power BI

An end-to-end project analyzing 124K+ LinkedIn job postings

To Collect job postings data from LinkedIn related to "Data" in "India" to gather various hidden informational insights.

Unveiling job market trends with Scrapy and AWS

analysis of the linkedin jobs

Bot to scrap jobs from linkedin and make a distribution analysis of abilities

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AI/ML Job Postings Analysis on the 1.3M LinkedIn Jobs and Skills 2024

Scrape linkedin job posting for applying jobs and analysis of current hot skills for DE

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The objective of this analysis is to gain insights into job postings on LinkedIn and understand patterns and trends related to job availability, application counts, contract types, experience levels, and sector distribution.