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.

Taxonomy of the Dataset https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13623947%2F85fde0e9bcd9e6532b63e65ca1e5b58a%2FWhatsApp%20Image%202024-02-27%20at%2012.12.59.jpeg?generation=1709016197299811&alt=media" alt="">

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

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

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 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 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

Merged files from https://www.kaggle.com/datasets/asaniczka/1-3m-linkedin-jobs-and-skills-2024

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.

Dataset

This dataset was created by davideev9

Contents

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.

Dataset

This dataset was created by Steve Marcello Liem

Contents

Dataset Description: "LinkedIn Canada: Data Science Jobs 2024"

Overview: The "LinkedIn Canada: Data Science Jobs 2024" dataset presents an insightful overview of the data science job market in Canada as sourced from LinkedIn. This dataset, comprising 300 unique entries, meticulously details various aspects of job postings including company information, job titles, locations, contract types, experience levels, and industry sectors. It serves as a compact yet rich resource for understanding the landscape of data science employment opportunities in Canada at the beginning of 2024.

Data Science and Analysis Possibilities: Given its focused scope, this dataset is ideally suited for targeted data analysis and research within the realm of the Canadian data science job market. Analysts and researchers can utilize this dataset to: - Identify trends in job availability across different provinces or cities in Canada. - Analyze the distribution of job types and roles within the data science field. - Compare qualifications and experience levels sought by employers. - Investigate sector-specific demand for data science skills. While the dataset's size may limit broad generalizations, it offers an excellent opportunity for niche analyses and case studies.

Column Descriptors: The dataset contains the following key columns:

-Company Name: The name of the company posting the job.
-Job Title: The title of the job posting.
-Location: Geographical location of the job.
-Contract Type: Type of employment contract offered (e.g., Full-time, Part-time).
-Experience Level: Required experience level for the job (e.g., Entry-level, Mid-Senior level).
-Sector: Industry sector of the job posting.
-Description: Brief description of the job role and responsibilities.
-Applications Count: Number of applicants for the job.
-Published At: The date when the job was posted

Ethical Data Collection: Adhering to ethical data collection practices, this dataset was gathered using Apify, ensuring that it conforms to LinkedIn’s data use policies and respects user privacy. This approach guarantees that the dataset is not only accurate and relevant but also responsibly sourced.

Acknowledgments: We are grateful to LinkedIn and Apify for their essential roles in providing and facilitating access to such valuable job market data. Their contribution is pivotal in enabling a deeper understanding of employment trends in the data science sector.

Image Credit: The image visualizing this dataset was created using Dall-E 3, reflecting the innovative intersection of artificial intelligence and art. This visual aid enhances the presentation of the dataset, symbolizing its thematic focus and contemporary relevance.

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}
}

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 offers a detailed collection of job listings from LinkedIn, covering the period from August 1st to August 15th, 2023. With nearly 3 million records, this dataset is an invaluable resource for professionals in human resources, labor market analysis, data science, and related fields who are looking to explore job market trends, analyze skills demand, and study employment opportunities across a broad range of industries.

Key Features:

Job Information: Includes job titles, descriptions, categories, and unique job identifiers, offering detailed insights into the nature of the job postings. Company Data: Comprehensive information about the hiring companies, including names, industries, and locations. Job Requirements: Data on necessary skills, qualifications, experience levels, and types of employment. Geographic Coverage: Extensive details on job locations across various countries and regions, making it possible to conduct geographic analyses of job opportunities. Application Details: Information regarding application processes and deadlines where available. Time of Data Collection: Each job listing is time-stamped, reflecting the active job postings on LinkedIn between August 1st and August 15th, 2023.

Dataset Overview:

Price: $1500.0 Total Records Count: 2,862,984 Domain Name: LinkedIn Date Range: August 1st, 2023 - August 15th, 2023 File Extension: LDJSON (Line-Delimited JSON)

Use Cases:

Job Market Analysis: Delve into trends, skills demand, and emerging job roles across different industries for early August 2023. Recruitment Strategy Development: Improve recruitment approaches by understanding the competitive landscape and job posting dynamics. Skill Demand Insights: Identify which skills and qualifications were most in demand across various sectors during the data period. Labor Market Research: Conduct thorough research on employment trends, job availability, and distribution of job opportunities by region. Economic and Workforce Analysis: Use job listings data to gauge economic activity and workforce trends during this period.

About the Data Collection:

This dataset was meticulously compiled using advanced web scraping techniques to ensure accuracy, relevance, and comprehensive coverage. For those requiring custom datasets or specific data extraction from platforms like LinkedIn, PromptCloud provides tailored web scraping solutions. These services are designed to meet the unique data needs of businesses and researchers, delivering high-quality, structured data ready for analysis. https://www.promptcloud.com/contact/

Disclaimer: This dataset is provided for research and educational purposes only. Users must ensure their use of this data complies with LinkedIn’s terms of service and all relevant laws and regulations.

Over 500 jobs scraped from the job section of LinkedIn.

Attribute Feature's Meaning location The location of the job designation The designation of the job name Name of the company industry Industry in which the company operates employees_count Count of employees linkedin_followers Number of followers on linkedin involvement the nature of involvement in the job, for instance: Full-time, part-time level The seniority level like Mid-Senior level total_applicants total number of applicants Skills Skills required for the job

The LinkedIn Jobs for Tech Degrees in Saudi Arabia dataset is a collection of job listings scraped from the popular professional networking website, LinkedIn. The dataset consists of seven columns, including: - job title - job URL - company URL - company name - location - active hiring status - date.

This dataset specifically focuses on jobs in the technology industry in Saudi Arabia, making it a valuable resource for job seekers and recruiters alike.

The job title column provides information about the position being advertised, while the** job URL column** links to the original job listing on LinkedIn.

The company URL column links to the company's LinkedIn page, providing additional information about the hiring organization.

The company name column provides the name of the hiring organization, while the location column specifies the city and region of the job listing.

The actively hiring status column indicates whether the company is actively seeking candidates for the position or has already filled it. Finally, the **date column **shows the date the job was posted on LinkedIn.

With this dataset, job seekers in the technology industry can easily search for open positions in Saudi Arabia, while recruiters can use the data to identify trends and patterns in the job market. Overall, the LinkedIn Jobs for Tech Degrees in Saudi Arabia dataset is a valuable resource for anyone looking to gain insights into the tech job market in Saudi Arabia.

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 science 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 science 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 Shahadat Rahman on Unsplash

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