LinkedIn is a widely used professional networking platform that hosts millions of job postings. This dataset contains 1.3 million job listings scraped from LinkedIn in the year 2024.

This dataset can be used for various research tasks such as job market analysis, skills mapping, job recommendation systems, and more.

If you find this dataset valuable, please upvote 😊💼

This is the same master dataset that powers SkillExplorer

Interesting Task Ideas:

1. Practice data cleaning on raw data.
2. Analyze the most in-demand job titles or industries in different cities or countries.
3. Identify the top companies hiring for specific job positions.
4. Utilize the skills data to determine the most sought-after skills in different job categories.
5. Build a job recommendation system based on user profiles and job listing data.
6. Discover patterns in job types or levels across different industries.
7. Identify skill gaps in the job market to inform educational or training programs.
8. Explore the relationship between job title and required skills.

Photo by Clem Onojeghuo on Unsplash

The data comprises job-related information from LinkedIn job postings scraped over a 2-day period. Key features include company details and job-specific information like title, description, and salary. The dataset provides a comprehensive view for exploring factors influencing job posting characteristics and has been reformatted from its original source to improve its compatibility among various machine learning algorithms.

LinkedIn Data Jobs Dataset

Scraped LinkedIn job postings for data-related roles (Data Analyst, Data Engineer, Data Scientist, etc.)

Overview

This dataset contains job postings scraped from LinkedIn, including job titles, companies, locations, descriptions, and job types (remote/hybrid/onsite). The data can be used for data cleaning, NLP analysis, skill extraction, and building AI-powered job application tools. ## Dataset Features Column Name Description Title Job title (e.g., "Data Analyst," "Product Analyst") Company Hiring company name Location Job location (city/country) Description Full job description (may include company info) Job Type Remote, Hybrid, or Onsite (if available)

Potential Use Cases

✅ Data Cleaning & Normalization – Standardize job titles, locations, and descriptions. ✅ NLP & Skill Extraction – Find the most in-demand skills (Python, SQL, ML, etc.). ✅ Job Type Analysis – Compare remote vs. onsite job trends. ✅ AI-Powered Job Tools – Build a Streamlit app to generate:

"About Me" sections tailored to job descriptions.

Auto-generated cover letters based on job requirements.

GitHub Collaboration Want to contribute? Join the project here: 🔗 https://github.com/JoyKimaiyo/Web-scraping-data-jobs-and-automating-about-me-section

Acknowledgments Data scraped from LinkedIn for educational/non-commercial use.

Data engineering is a rapidly growing field in the tech industry, and LinkedIn is a popular platform for finding job opportunities in this domain.

This dataset provides valuable insights into data engineering job postings, including the required skills and software proficiency sought by employers.

If you find this dataset useful, don't forget to hit the upvote button! 😊💝

Checkout my top datasets

• Top Spotify Songs in 73 Countries
• Wages by Education in the USA
• Amazon Products Dataset (1.4M Products)
• TMDB 950K Movies
• Amazon Kindle Books (130K Books)

Interesting Task Ideas:

1. Analyze the most in-demand skills and software for data engineering positions.
2. Find common job titles and identify emerging job roles in the data engineering field.
3. Explore the geographical distribution of data engineering job opportunities.
4. Determine the average job level and types of data engineering positions available.
5. Identify the most sought-after skills for entry-level, mid-level, and senior-level data engineering roles.

Photo by Ben Sweet on Unsplash

Data science is a rapidly growing field in the tech industry, and LinkedIn is a popular platform for finding job opportunities in this domain.

This dataset provides valuable insights into data analyst job postings, including the required skills and software proficiency sought by employers.

If you find this dataset useful, don't forget to hit the upvote button! 😊💝

Checkout my top datasets

• Top Spotify Songs in 73 Countries
• Wages by Education in the USA
• Amazon Products Dataset (1.4M Products)
• TMDB 950K Movies
• Amazon Kindle Books (130K Books)

Interesting Task Ideas:

1. Analyze the most in-demand skills and software for data analyst positions.
2. Find common job titles in the data science field.
3. Explore the geographical distribution of data engineering job opportunities.
4. Identify the most sought-after skills

Photo by Lukas Blazek on Unsplash

LinkedIn Job Postings Dataset

Description

This dataset contains information about job postings on LinkedIn. The data is divided into several files, each containing different aspects of the job postings:

1. job_postings.csv: This file contains detailed information about each job posting, including the job title, description, salary, work type, location, and more.
2. companies.csv: This file contains detailed information about each company that posted a job, including the company name, website, description, size, location, and more.
3. company_industries.csv: This file contains the industries associated with each company.
4. company_specialities.csv: This file contains the specialties associated with each company.
5. employee_counts.csv: This file contains the employee and follower counts for each company.
6. benefits.csv: This file contains the benefits associated with each job.
7. job_industries.csv: This file contains the industries associated with each job.
8. job_skills.csv: This file contains the skills associated with each job.

Usage

This dataset can be used for various purposes such as: - Analyzing the job market - Analyzing company trends - Analyzing salary trends - Building a job recommendation system - Natural Language Processing (NLP) tasks such as keyword extraction, topic modeling, etc.

Acknowledgements

This dataset was collected from LinkedIn. Please note that the data may be subject to LinkedIn's terms of use.

License

This dataset is released under the Open Database License (ODbL).

This dataset contains a collection of software engineering job listings scraped from LinkedIn. It provides valuable insights into the current job market, job requirements, and company hiring trends.

If you find this dataset useful, don't forget to hit the upvote button! 😊💝

Checkout my top datasets

• Top Spotify Songs in 73 Countries
• Wages by Education in the USA
• Amazon Products Dataset (1.4M Products)
• TMDB 950K Movies
• Amazon Kindle Books (130K Books)

Interesting Task Ideas:

1. Analyze the most in-demand software engineering job titles.
2. Explore the geographical distribution of software engineering job opportunities.
3. Identify the most sought-after programming languages and skills in job descriptions.
4. Determine the average years of experience required for different job levels.

Photo by Hack Capital on Unsplash

Collated 8 different data source. Filtered for only Data and ML jobs, titles and descriptions. Applied text data cleaning and preprocessing, documented here: https://tianyimasf.github.io/ai/data-cleaning/.

1. LinkedIn-Tech-Job-Data: A compilation of job posts and metadata scraped from various tech categories on LinkedIn

2. Data Analyst Jobs: This dataset was created by picklesueat and contains more than 2000 job listing for data analyst positions

3. US Job Postings from 2023-05-05: This dataset is an excerpt of our web scraping activities at Techmap.io and contains a sample of 33k Job Postings from the USA on May 5th 2023.

4. LinkedIn Job Postings Dataset: This dataset contains information about job postings on LinkedIn.

5. LinkedIn Job Postings - Machine Learning Data Set: The data comprises job-related information from LinkedIn job postings scraped over a 2-day period.

6. Linkedin Canada: Data Science Jobs 2024: The "LinkedIn Canada: Data Science Jobs 2024" dataset presents an insightful overview of the data science job market in Canada as sourced from LinkedIn.

7. Data Scientist - Linkedin Job Postings: This dataset provides valuable insights into data science job postings, including the required skills and software proficiency sought by employers.

8. LinkedIn Job Postings Dataset: This dataset contains information about job postings on LinkedIn.

Initially used for my project analyzing data job market, including analyzing titles, skills, and company functions. Could be used for other purposes like posting generation.

The following dataset is extracted using an API and contains job data from LinkedIN about 10 common job roles in Inida.

The data can be used for a comprehensive analysis on application trends, peak posting times, popular job titles, company dynamics, geographical patterns, sector-specific insights, job freshness, company-specific behaviors, and predictive modeling. Predictive modeling can be used to anticipate job market dynamics. In summary, this dataset facilitates a thorough exploration of the job market, providing actionable insights for both job seekers and employers.

Dataset Columns

id: Unique identifier for each job posting (Integer).

publishedAt: Date when the job was published (String, formatted as 'YYYY-MM-DD').

title: Job title (String).

companyName: Name of the hiring company (String).

postedTime: Time since the job was posted (String).

applicationsCount: Number of job applications received (Float).

description: Job description, including required skills (String).

contractType: Type of employment contract (String).

experienceLevel: Level of experience required for the job (String).

workType: Type of work arrangement (String).

sector: Industry sector of the job (String).

companyId: Unique identifier for the hiring company (Integer).

city: City where the job is located (String).

state: State where the job is located (String).

recently_posted_jobs: Indicates whether the job is recently posted (String, 'Yes' or 'No').

The Employment Growth LinkedIn dataset contains information about job postings related to employment growth, including:

About Column: - isic_section: A to X - isic_section_name: Agriculture; forestry and fishing, Mining and quarrying - isic_division: Show the division number. - isic_division_name: Crop and animal production, hunting and related service activities, Mining of coal and lignite, - industry_sk - industry_name: ranching, mining & metals, oil & energy, dairy, farming, etc - Industry_group_sk: Show the digits. - Industry_group_name: Manufacturing, Corporate services, Consumer goods,

This dataset can be used to analyze:

• Job market trends and growth areas
• In-demand skills for employment growth
• Geographic distribution of employment growth
• Industry-specific employment growth metrics

*This dataset can be used for various purposes such as: * - Job market analysis - Workforce planning - Economic development - Research and development

This comprehensive dataset contains a curated collection of 100 job postings for Data Analyst positions, sourced from LinkedIn. As the demand for skilled data analysts continues to surge, this dataset serves as a valuable resource for data enthusiasts, aspiring data analysts, and researchers alike.

The dataset contains information on 30,000+ job postings collected from LinkedIn till the year 2023 which provides a rich source of information on job postings on LinkedIn, with concise information on the job title, company, location, and other key attributes of each posting. This data can be used to gain insights into employment trends and dynamics, identify key skills and experiences that are in high demand, and optimize job postings to attract the right candidates. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F18065122%2Ff51a9373d9b0bbc78235ae4be8dbdce5%2F1.jpeg?generation=1751200071553062&alt=media" alt="">

Dataset

This dataset was created by davideev9

Contents

Job Skill Set

Description

The Job Skill Set Dataset is designed for use in machine learning projects related to job matching, skill extraction, and natural language processing tasks. The dataset includes detailed information about job roles, descriptions, and associated skill sets, enabling developers and researchers to build and evaluate models for career recommendation systems, resume parsing, and skill inference.

Dataset Source

This dataset was initially sourced from the Kaggle dataset titled LinkedIn Job Postings by Arshkon. The original job postings data has been enhanced by extracting skill sets using RecAI API services. These APIs are designed for skill parsing, resume analysis, and other recruitment-related tasks.

Dataset

The dataset contains the following features: - job_id: A unique identifier for each job posting. - category: The category of the job, such as INFORMATION-TECHNOLOGY,BUSINESS-DEVELOPMENT,FINANCE,SALES or HR. - job_title: The title of the job position. - job_description: A detailed text description of the job, including responsibilities and qualifications. - job_skill_set: A list of relevant skills(include hard and soft skills) associated with the job, extracted using RecAI APIs.

Use Cases

This dataset is particularly useful for the following applications:

• Skill Extraction: Identifying and parsing skills from job descriptions.
• Job-Resume Matching: Matching job descriptions with potential candidate profiles.
• Recommendation Systems: Developing models that recommend jobs or training programs based on required skills.
• Natural Language Processing: Experimenting with text-based models in recruitment and career analytics.

License

Please consult the license information on the original Kaggle dataset page here.

Citation

If you use this dataset, please cite it as follows:

@misc{batuhan_mutlu_2024,
  title={job-skill-set},
  url={https://www.kaggle.com/dsv/10201355},
  DOI={10.34740/KAGGLE/DSV/10201355},
  publisher={Kaggle},
  author={Batuhan Mutlu},
  year={2024}
}

Dataset

This dataset was created by AJ Strauman-Scott

Released under Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC-SA 3.0 IGO)

Contents

Dataset

This dataset was created by Alex Ma

Released under Apache 2.0

Contents

This dataset provides an extensive collection of job listings from LinkedIn, covering the period from August 15th to August 31st, 2023. With nearly 3 million records, this dataset is a valuable resource for HR professionals, data scientists, labor market analysts, and researchers looking to explore job market trends, skills demand, and employment opportunities across various industries.

Key Features:

Job Information: Detailed job titles, descriptions, categories, and unique job identifiers. Company Data: Information on hiring companies, including company names, industries, and locations. Job Requirements: Data on required skills, qualifications, experience levels, and employment types. Job Locations: Comprehensive coverage of job locations across various countries and regions. Application Details: Information on application processes and deadlines (if available). Time of Data Collection: Listings are time-stamped, reflecting the job postings available from August 15th to August 31st, 2023.

Dataset Overview:

Price: $2500.0 Total Records Count: 2,862,984 Domain Name: LinkedIn Date Range: August 15th, 2023 - August 31st, 2023 File Extension: LDJSON (Line-Delimited JSON)

Use Cases:

Job Market Analysis: Analyze job market trends, in-demand skills, and emerging roles across industries. Recruitment Strategies: Optimize recruitment strategies by understanding the competitive landscape and job posting patterns. Skill Demand Analysis: Identify the most sought-after skills and qualifications in various sectors. Labor Market Research: Conduct in-depth research on employment opportunities, job availability, and geographic job distribution. Economic Indicators: Use job listings data as an indicator of economic health and employment trends.

About the Data Collection:

This dataset was collected using sophisticated web scraping techniques to ensure comprehensive coverage and accuracy. For businesses and researchers needing customized data or large-scale web extraction from platforms like LinkedIn, PromptCloud offers bespoke web scraping solutions. These services cater to specific needs, delivering high-quality, structured data tailored to unique research and business objectives. https://www.promptcloud.com/contact/

Disclaimer: This dataset is intended for research and educational purposes. Users are responsible for ensuring that their use of this data complies with LinkedIn’s terms of service and all applicable laws.

This dataset contains job postings from Linkedin from 2023 with the following features It can be used to analyze the current trends based on job positions, location,company nameetc

LinkedIn Job Salary Classification Using SVM and KNN This project uses machine learning to predict salary ranges (Low, Medium, High) for LinkedIn job postings by comparing Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) algorithms. Approach:

Extract features from job postings: title, description, skills, experience, location, and company size Preprocess and clean the dataset Train both SVM and KNN models on labeled data Evaluate performance using accuracy, precision, recall, and F1-score

Goal: Develop an automated system to help job seekers understand salary expectations and assist recruiters in creating competitive compensation packages.

Dataset

This dataset was created by Steve Marcello Liem

Contents