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.

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

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

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

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.

This repository contains the cleaned LinkedIn Job Postings Dataset, which has been prepared and processed for analysis. The dataset is sourced from LinkedIn job postings and has undergone data cleaning and manipulation to enhance its quality and suitability for various analytical tasks.

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.

📊 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.

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.

An in-depth visual analysis and data storytelling project analyzing LinkedIn job postings. Looking into industry trends, correlations, and job market insights

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

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Repository presents a data analysis on LinkedIn job postings, from Kaggle. It includes preliminary analysis. Setting specific hypothesis. Deeper statistical analysis. Testing and evaluating hypothesis. Done with Python, within a Jupyter Notebook environment. It was done as exercise for Data Science Role. :)

Performed an exploratory data analysis on Linkedin Job postings

This projects includes how I web scraped Linkedin job openings for data scientists using Selenium and some analysis of its meta data using pandas, NumPy and Matplotlib

An analysis of job postings on Linkedin

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

Data Analysis using Kaggle Dataset showing LinkedIn Data Analyst Job Postings from late 2022

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

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

An exploratory analysis of the 2024 job market using job postings scraped from LinkedIn, with an emphasis on the Data Job market and the skills/tools currently in demand.

The objective of the analysis is to combine and clean LinkedIn job postings and job skills datasets, and prepare the data for further exploration and modeling. This ensures actionable insights into job market trends.

SkillFinder extracts and visualizes in-demand skills from LinkedIn job postings using LLM-powered analysis. Discover what employers want through interactive visualizations and natural language querying, turning job market data into actionable career insights.

Power BI analysis of LinkedIn job postings (Apr–May 2025) revealing top data roles, hiring companies, and weekly trends. Interactive dashboard built with DAX measures and clean data modeling. Ideal for job seekers, analysts, and recruiters

Analyze LinkedIn job postings to identify top in-demand skills, highest-paying job titles, and salary trends. Built in Python with Pandas and Matplotlib, designed to be modular and extendable for future analysis or machine learning features.

An end-to-end analysis of over 8,400 LinkedIn job postings to identify key trends in the global Data Analyst job market. Features data cleaning with Python/Pandas and an interactive dashboard built in Power BI to visualize insights.

India Job Market Analysis End-to-end data project analyzing LinkedIn job postings across India. Includes cleaned datasets, Python EDA, and a multi-page Power BI dashboard revealing insights on job roles, top skills, hiring trends, salaries, and experience levels. Clear structure with visuals and demo video.

This project repository involves analyzing job postings data scrapped from LinkedIn. The analysis was conducted in two phases: data cleaning and exploratory data analysis (EDA). The insights were visualized using Python and an interactive dashboard was created using Power BI.

An automated job scraping and analysis pipeline that extracts postings from LinkedIn/Glassdoor, cleans and validates data, and uses LLM-powered relevance scoring to match roles with a candidate’s skills. Includes data visualization for insights, SQL storage, and NLP-driven job matching.