Context

There's a story behind every dataset and here's your opportunity to share yours.

Content

This dataset contains 10,000 people on LinkedIn as well as the jobs held by that person on the 1st of January 2018. It was scraped using a browser extension. A rough example of which can be found here https://chrome.google.com/webstore/detail/edna-scrape-ext/hcchbehfooacdlebbpgodbfleicooahi.

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

In today's dynamic business landscape, having access to actionable insights is paramount. The LinkedIn Professional Profiles Dataset is your gateway to a treasure trove of information, encompassing key details about professionals' careers, education, skills, and more. This dataset caters to a diverse range of business needs, including tracking talent movement, sourcing new talent, lead generation, and even serving as an unconventional investment data source.

Key Data Points: Name: Full name of the professional. Title: Current job title. Position: Detailed job position within the company. Current Company: Name of the current employing company. Avatar: Profile picture URL for visual identification. Experience: Chronological list of past job experiences. Education: Educational background and institutions attended. Location: Geographic location of the professional. and some more which you should explore........

With the LinkedIn dataset at your fingertips, you can generate investment signals, refine talent sourcing strategies, and improve lead generation tactics. Tailor your analyses to your specific business objectives and gain a competitive edge through data-driven decision-making.

Unlock the full potential of LinkedIn data with our extensive dataset that combines profiles, company information, and job listings into one powerful resource for business decision-making, strategic hiring, competitive analysis, and market trend insights. This all-encompassing dataset is ideal for professionals, recruiters, analysts, and marketers aiming to enhance their strategies and operations across various business functions. Dataset Features

Profiles: Dive into detailed public profiles featuring names, titles, positions, experience, education, skills, and more. Utilize this data for talent sourcing, lead generation, and investment signaling, with a refresh rate ensuring up to 30 million records per month. Companies: Access comprehensive company data including ID, country, industry, size, number of followers, website details, subsidiaries, and posts. Tailored subsets by industry or region provide invaluable insights for CRM enrichment, competitive intelligence, and understanding the startup ecosystem, updated monthly with up to 40 million records. Job Listings: Explore current job opportunities detailed with job titles, company names, locations, and employment specifics such as seniority levels and employment functions. This dataset includes direct application links and real-time application numbers, serving as a crucial tool for job seekers and analysts looking to understand industry trends and the job market dynamics.

Customizable Subsets for Specific Needs Our LinkedIn dataset offers the flexibility to tailor the dataset according to your specific business requirements. Whether you need comprehensive insights across all data points or are focused on specific segments like job listings, company profiles, or individual professional details, we can customize the dataset to match your needs. This modular approach ensures that you get only the data that is most relevant to your objectives, maximizing efficiency and relevance in your strategic applications. Popular Use Cases

Strategic Hiring and Recruiting: Track talent movement, identify growth opportunities, and enhance your recruiting efforts with targeted data. Market Analysis and Competitive Intelligence: Gain a competitive edge by analyzing company growth, industry trends, and strategic opportunities. Lead Generation and CRM Enrichment: Enrich your database with up-to-date company and professional data for targeted marketing and sales strategies. Job Market Insights and Trends: Leverage detailed job listings for a nuanced understanding of employment trends and opportunities, facilitating effective job matching and market analysis. AI-Driven Predictive Analytics: Utilize AI algorithms to analyze large datasets for predicting industry shifts, optimizing business operations, and enhancing decision-making processes based on actionable data insights.

Whether you are mapping out competitive landscapes, sourcing new talent, or analyzing job market trends, our LinkedIn dataset provides the tools you need to succeed. Customize your access to fit specific needs, ensuring that you have the most relevant and timely data at your fingertips.

Dataset Description

This dataset contains profile and employment information for 10,000 LinkedIn users, representing their professional status as of January 1, 2018. The data includes demographic estimates, job roles, company attributes, connection metrics, and location details.

Collected through a browser-based scraping extension, the dataset provides a structured view of professional networks and employment patterns. It enables analysis of career progression, company workforce characteristics, hiring trends, and professional networking behavior.

The dataset is particularly useful for research in labor market analytics, social network analysis, recruitment intelligence, and machine learning applications involving professional profile data.

Key Features

Contains data for 10,000 LinkedIn members

Includes both individual profile attributes and company information

Captures job roles active on a specific historical date

Provides networking indicators such as connections and followers

Enables career trajectory and employment duration analysis

Useful for analytics, recommendation systems, and HR research

Generate targeted lead lists on demand by searching through our LinkedIn database of millions of profiles along with their profile details, work and personal emails, phone number etc.

We extracted data to conduct market research and needed detailed data about multiple LinkedIn profiles. Stop copy-pasting data into a Google Sheet. Instead, start scraping LinkedIn profiles and boosting your automation journey with Lead for Business.

Data attributes we provide:

Name Job Title Email Phone Summary Profile Url Job History Education History Skills Certification Location and More

Full profile of 10,000 people in the US - download here, data schema here, with more than 40 data points including - Full Name - Education - Location - Work Experience History and many more!

There are additionally 258+ Million US people profiles available, visit the LinkDB product page here.

Our LinkDB database is an exhaustive database of publicly accessible LinkedIn people and companies profiles. It contains close to 500 Million people and companies profiles globally.

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.

The LinkedIn Jobs Listing dataset emerges as a comprehensive resource for individuals navigating the contemporary job market. With a focus on critical employment details, the dataset encapsulates key facets of job listings, including titles, company names, locations, and employment specifics such as seniority levels and functions. This wealth of information is instrumental for job seekers looking to align their skills and aspirations with the right opportunities. The inclusion of direct application links and real-time application numbers enhances the dataset's utility, offering users a streamlined approach to engaging with potential employers. Beyond aiding job seekers, the dataset serves as a valuable tool for analysts and researchers, providing nuanced insights into industry trends and the evolving demands of the job market. The temporal aspect, captured through job posting timestamps, allows for the observation of job trends over time. Moreover, the dataset's integration of company details, including unique identifiers and LinkedIn profile links, enables a deeper exploration of hiring organizations. Whether for job seekers or analysts, the LinkedIn Jobs Listing dataset emerges as a versatile and informative repository, empowering users with the knowledge to make informed decisions in their professional pursuits.

Data that captures the evolution of skill requirements over time across the workforce based on updates to LinkedIn member profiles. This dataset is part of the LinkedIn - World Bank Group partnership, which helps governments and researchers understand rapidly evolving labor markets with detailed and dynamic data. It allows leaders to benchmark and compare labor markets across the world; analyze skills, occupations, migration, and industries; and leverage real-time data to make policy changes. Visualizations for many of these data are available at linkedindata.worldbank.org. The data cover 2015-2019, are refreshed on an annual basis, and are available for 140+ countries. | This dataset contains important information and resources. For comprehensive details, documentation, and inquiries, please contact data@worldbank.org. Additional metadata and related resources are available on this page.

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 LinkedIn posts dataset is a comprehensive collection of user-generated content on LinkedIn, featuring key fields such as post ID, user ID, URL, title, post text, date posted, hashtags, and engagement metrics like the number of likes and comments. This dataset also includes additional elements such as embedded links, images, videos, top visible comments, and links to more posts by the user or relevant content. It is ideal for social media analysts, marketers, and researchers looking to analyze user behavior, content trends, and engagement on LinkedIn.

LinkedIn data will be a strong resource for businesses and marketers. Such data is useful as it consists of user profiles, job titles, and company information. LinkedIn is a platform that has around 900 million users around the globe, making this one of the largest networks available. With this material, you can create specific campaigns that speak to professionals. You can take advantage of this database because it is kept fresh, which means it still has corrected contacts and individuals. You are using LinkedIn data that gives you access to business decision-makers and industry leaders. Incorporating this dataset into your marketing plan allows you to consolidate outreach efforts. Find your LinkedIn datasets and revamp your outreach strategy at List To Data! LinkedIn number database assists in reaching the target audience and building relationships; this directory provides you with vital information, including contact and user profiles. An essential database, particularly for B2B marketers. You will have access to a comprehensive list of all the LinkedIn members. By using this data, you can better customize your messaging and increase response rates. Furthermore, this resource is updated often, giving your campaigns access to new leads. You may make your outreach efforts more efficient by using this dataset in your marketing strategy. To improve your B2B marketing success and gain access to premium LinkedIn number databases, visit List To Data!

Dataset

This dataset was created by Lakshay Handa

Released under Apache 2.0

Contents

Power your US Operations, HR Tech, and Market Intelligence engines with the most comprehensive database of the American workforce. This dataset offers a structured, historical view of 194,408,909 US professionals, capturing career trajectories, educational backgrounds, and skill sets across every state and industry.

With coverage nearing 100% of the active US white-collar workforce, our US Professional Identity Graph provides a dynamic view of talent. We map the relationships between People, Companies, Skills, and Schools, allowing you to answer complex questions about domestic talent migration, skill supply, and organizational hierarchies.

Key Use Cases 1. B2B Data Enrichment & CRM Hygiene Turn a simple email address or name into a full 360-degree US prospect profile.

Append: Add currentCompanies, jobTitle, and industry to your existing US leads.

Lead Scoring: Use connectionsCount and recommendations as proxies for influence within US markets.

Refresh: Identify when a prospect has changed jobs (lastUpdated) to trigger "New Role" outreach campaigns.

1. Talent Intelligence & Recruitment Build the next generation of US hiring tools.

Sourcing: Query by complex skill combinations (e.g., "Python" + "TensorFlow" + "5 Years Experience" in "San Francisco").

Alumni Targeting: Use educations data to find candidates from specific US Universities (Ivy League, State Colleges, etc.).

DEI Analytics: Leverage pronoun and volunteerExperiences data for diversity and inclusion benchmarking.

1. US Labor Market Analysis

Migration Trends: Track talent movement between states (e.g., "Tech talent moving from CA to TX").

Skill Trends: Analyze the rise of specific skills across US industries.

Data Dictionary & Schema Attributes Our schema is normalized for easy ingestion. We provide over 30 rich attributes per profile, grouped into five core intelligence clusters:

1. Identity & Social (The "Who")

publicId / vanity: The unique handle for the profile (e.g., /in/john-doe).

urn: The immutable, system-unique identifier.

fullName, firstName, lastName: Parsed name fields.

headline & summary: The professional's self-described bio and taglines.

pronoun: Self-identified pronouns.

logoUrl: Profile image link.

openToWork: Indicator of active job-seeking status.

1. Professional Graph (The "What")

currentCompanies: Detailed object containing Company Name, Title, Start Date.

previousCompanies: Historical array of past roles, creating a full resume view.

industry: Standardized industry classification.

1. Capability & Skills (The "How")

skills: Array of endorsed skills (e.g., "Project Management", "SQL").

languages: Spoken languages and proficiency levels.

certifications: Professional licenses and validity dates.

courses & honors: Academic and professional awards.

educations: Full academic history including Degree, School, and Dates.

1. Influence & Content (The "Reach")

connectionsCount: Total network size.

followersCount: Measure of audience reach.

recommendations: Text of received professional endorsements.

organizations: Memberships in professional bodies or non-profits.

patents, projects, publications: Intellectual property and portfolio items.

1. Location & Metadata

locationName: City/Metro area (e.g., "Greater New York City Area", "Austin, Texas").

locationCountry: Fixed to "US".

lastUpdated: Timestamp of the most recent data refresh.

id: 194408909 - Fill Rate: 100% fullName: 194392269 - Fill Rate: 99.99% firstName: 194391083 - Fill Rate: 99.99% lastName: 193031965 - Fill Rate: 99.29% publicId: 194408909 - Fill Rate: 100% urn: 194408909 - Fill Rate: 100% headline: 194260405 - Fill Rate: 99.92% summary: 41525593 - Fill Rate: 21.36% industry: 143067057 - Fill Rate: 73.59% locationName: 194408824 - Fill Rate: 100% locationCountry: 194408909 - Fill Rate: 100% logoUrl: 62644925 - Fill Rate: 32.22% connectionsCount: 139069652 - Fill Rate: 71.53% followersCount: 140881048 - Fill Rate: 72.47% currentCompanies: 133983286 - Fill Rate: 68.92% previousCompanies: 67758867 - Fill Rate: 34.85% educations: 88604497 - Fill Rate: 45.58% volunteerExperiences: 12375279 - Fill Rate: 6.37% skills: 75429843 - Fill Rate: 38.8% pronoun: 14806274 - Fill Rate: 7.62% related: 141341109 - Fill Rate: 72.7% languages: 14267971 - Fill Rate: 7.34% recommendations: 10304568 - Fill Rate: 5.3% certifications: 19279558 - Fill Rate: 9.92% courses: 5153692 - Fill Rate: 2.65% honors: 7139463 - Fill Rate: 3.67% organizations: 6840143 - Fill Rate: 3.52% patents: 411407 - Fill Rate: 0.21% projects: 4099324 - Fill Rate: 2.11% publications: 2927800 - Fill Rate: 1.51% lastUpdated: 194408909 - Fill Rate: 100% member_id: 193803832 - Fill Rate: 99.69% company_id: 85095974 - Fill Rate: 43.77% num_recommenders: 10304568 - Fill Rate: 5.3% experiences_count: 146291011 - Fill Rate: 75.25% educations_count: 88604834 - Fill Rate: 45.58% linkedin_name: 194408909 - Fill Rate: 100% endorsers: 6508123 - Fill Rate: 3.35% open_to_work: 6433122 - Fill Rate: 3.3...

Context

Anonymized data from profiles scraped on LinkedIn. Contains data from about 15000 profiles. Profiles came from people predominantly located in Australia. Includes all their work history as well as analysis of their photo and name.

Content

Each row contains:

• Profile data
• Job data
• Name analysis (Race, Gender)
• Profile picture analysis (Age, Race, Gender, Attractiveness, Health, Emotionality)

Acknowledgements

We wouldn't be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.

Inspiration

Your data will be in front of the world's largest data science community. What questions do you want to see answered?

rribeiol/linkedin-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

Scale your HR Tech, B2B Sales, and Market Intelligence engines with the world’s most comprehensive database of public professional profiles. This dataset offers a structured, historical view of the global workforce, capturing the career trajectories, educational backgrounds, and skill sets of over 830,042,175 professionals across 190+ countries.

Unlike static contact lists, our Professional Identity Graph provides a dynamic view of an individual's career. We map the relationships between People, Companies, Skills, and Schools, allowing you to answer complex questions about talent migration, skill supply, and organizational hierarchies.

All profiles are matched to a public Linkedin URL

Key Use Cases 1. B2B Data Enrichment & CRM Hygiene Turn a simple email address or name into a full 360-degree prospect profile.

Append: Add currentCompanies, jobTitle, and industry to your existing leads.

Lead Scoring: Use connectionsCount and recommendations as proxies for influence and decision-making power.

Refresh: Identify when a prospect has changed jobs (lastUpdated) to trigger "New Role" outreach campaigns.

1. Talent Intelligence & Recruitment Build the next generation of hiring tools.

Sourcing: Query by complex skill combinations (e.g., "Python" + "TensorFlow" + "5 Years Experience").

Alumni Targeting: Use educations data to find candidates from target universities.

DEI Analytics: Leverage pronoun and volunteerExperiences data for diversity and inclusion benchmarking.

1. Investment & Labor Market Analysis

Headcount Growth: Track currentCompanies vs. previousCompanies to measure company growth or attrition rates in real-time.

Skill Trends: Analyze the rise of specific skills (e.g., "Generative AI") across specific industries or regions.

Data Dictionary & Schema Attributes Our schema is normalized for easy ingestion. We provide over 30 rich attributes per profile, grouped into five core intelligence clusters:

1. Identity & Social (The "Who")

publicId / vanity: The unique handle for the profile (e.g., /in/john-doe).

urn: The immutable, system-unique identifier.

fullName, firstName, lastName: Parsed name fields.

headline & summary: The professional's self-described bio and taglines.

pronoun: Self-identified pronouns (he/him, she/her, etc.).

logoUrl: Profile image link.

openToWork: Indicator of active job-seeking status.

1. Professional Graph (The "What")

currentCompanies: Detailed object containing Company Name, Title, Start Date.

previousCompanies: Historical array of past roles, creating a full resume view.

industry: Standardized industry classification.

1. Capability & Skills (The "How")

skills: Array of endorsed skills (e.g., "Project Management", "SQL").

languages: Spoken languages and proficiency levels.

certifications: Professional licenses and validity dates.

courses & honors: Academic and professional awards.

educations: Full academic history including Degree, School, and Dates.

1. Influence & Content (The "Reach")

connectionsCount: Total network size.

followersCount: Measure of audience reach.

recommendations: Text of received professional endorsements.

organizations: Memberships in professional bodies or non-profits.

patents, projects, publications: Intellectual property and portfolio items.

1. Location & Metadata

locationName: City/Metro area (e.g., "Greater New York City Area").

locationCountry: ISO-2 Country Code.

lastUpdated: Timestamp of the most recent data refresh.

fullName: 830042175 - Fill Rate: 99.99% firstName: 830023323 - Fill Rate: 99.98% lastName: 822995392 - Fill Rate: 99.14% publicId / vanity: 830159658 - Fill Rate: 100% urn: 830159658 - Fill Rate: 100% headline: 829660649 - Fill Rate: 99.94% summary: 154826408 - Fill Rate: 18.65% industry: 569584072 - Fill Rate: 68.61% locationName: 829491476 - Fill Rate: 99.92% locationCountry: 830159658 - Fill Rate: 100% logoUrl: 225683142 - Fill Rate: 27.19% connectionsCount: 563236676 - Fill Rate: 67.85% followersCount: 569950689 - Fill Rate: 68.66% currentCompanies: 544595655 - Fill Rate: 65.6% previousCompanies: 244822218 - Fill Rate: 29.49% educations: 378348844 - Fill Rate: 45.58% volunteerExperiences: 33804455 - Fill Rate: 4.07% skills: 296336188 - Fill Rate: 35.7% pronoun: 38741090 - Fill Rate: 4.67% related: 576329691 - Fill Rate: 69.42% languages: 73444194 - Fill Rate: 8.85% recommendations: 27940603 - Fill Rate: 3.37% certifications: 65446443 - Fill Rate: 7.88% courses: 21095553 - Fill Rate: 2.54% honors: 17348831 - Fill Rate: 2.09% organizations: 14691528 - Fill Rate: 1.77% patents: 1012239 - Fill Rate: 0.12% projects: 16879774 - Fill Rate: 2.03% publications: 9748127 - Fill Rate: 1.17% lastUpdated: 830159658 - Fill Rate: 100% openToWork: 42157137 - Fill Rate: 5.08%

Compliance & Data Governance We understand that compliance is paramount when handling professional data.

Source: All data is aggregated strictly from Public Web Sources. We do not hack, credential-stuff, or access data behind login walls....

Analysis of ‘Skills | LinkedIn Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://datacatalog.worldbank.org/search/dataset/0038027/ on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Data that captures the evolution of skill requirements over time across the workforce based on updates to LinkedIn member profiles.

This dataset is part of the LinkedIn - World Bank Group partnership, which helps governments and researchers understand rapidly evolving labor markets with detailed and dynamic data. It allows leaders to benchmark and compare labor markets across the world; analyze skills, occupations, migration, and industries; and leverage real-time data to make policy changes.

Visualizations for many of these data are available at linkedindata.worldbank.org. The data cover 2015-2019, are refreshed on an annual basis, and are available for 140+ countries.

--- Original source retains full ownership of the source dataset ---

The developers dataset is a comprehensive collection of technical professional profiles from LinkedIn, featuring key fields such as profile ID, name, position, technical skills, programming languages, certifications, current company, work experience, education, location, and connections. This dataset is filterable and customizable, allowing you to extract specific developer roles such as Software Engineers, DevOps Engineers, Data Scientists, Full Stack Developers, and other technical professionals. Filter by job titles, skills, programming languages, location, experience level, and more to create targeted datasets. Ideal for technical recruiters, HR departments, B2D marketing teams, market researchers, and companies looking to analyze the technical talent landscape or reach developers with relevant products and services.

Reddy-Sekhar-Gerivi/linkedin-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community