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.

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.

📊 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.

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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

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

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

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.

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

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.

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 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.

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.

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.

An Excel-based analysis of LinkedIn Data Analyst job postings to uncover top hiring companies, locations, and daily posting trends. The project includes data cleaning, pivot tables, and an interactive dashboard with a month slicer for dynamic insights.

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recently completed a comprehensive data analytics project where I analyzed the LinkedIn Job Postings (2023 dataset) to uncover insights about the current job market, hiring trends, top-demand skills, and organizational trends

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Data Analysis on LinkedIN Jobs Postings

The data comprises job-related information from LinkedIn job postings

Data_Analysis_LinkedIn_Job_Postings

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This project focuses on performing Exploratory Data Analysis (EDA) on job postings extracted from LinkedIn between 2023 and 2024, aiming to uncover trends in hiring practices, in-demand roles, and skill requirements across industries.