Canaria | Human Resources(HR) Data Indeed, LinkedIn & More | USA | 25M+ Monthly | AI-LLM Enhanced Deduplicated Unique Human Resources(HR) Data

Advanced Processing, Superior Insights Utilizing state-of-the-art AI and large language models (LLMs) validated by human experts, we are dedicated to delivering high-quality, actionable human resources (HR) data through innovative technology. Apart from the models included in our standard human resources (HR) data offerings, we have developed additional models to provide tailored results to your needs, such as a sentiment analysis model that analyzes text data to gauge sentiment, helping businesses understand public perception and employee feedback, anomaly detection models, and LLM-based summarization models that condense large chunks of human resources (HR) data for you. Our Models: • Deduplication Model: Our model first removes exact duplicate records, then uses advanced AI to identify and eliminate near-duplicate job postings across different URLs, achieving approximately a 60% deduplication rate, ensuring unique human resources (HR) data. • Title Taxonomy Model: With over 20 million unique job titles in our 500M+ job postings database, human resources (HR) data analysis can be challenging. Our AI models categorize each job posting into one of 50,000 standardized job titles from our internal normalized title taxonomy, simplifying human resources (HR) data analysis. • Skill Taxonomy Model: Our in-house AI model identifies key entities in job postings, including hard skills, soft skills, certifications, and qualifications. Unlike keyword-based approaches, our model not only finds relevant keywords but also excludes irrelevant ones, ensuring precise human resources (HR) data (e.g., "Hepatitis B" is a skill for nursing jobs but not for accounting jobs). • Job Category Model: Our AI models analyze job descriptions, entities, predicted salary, location, industry, and job title to determine the seniority level of a job, standardizing levels across different companies. Another model identifies if a job is remote, onsite, or hybrid, accounting for discrepancies between job classifications and descriptions (e.g., a job classified as onsite but open to remote), enhancing human resources (HR) data accuracy. • Salary Estimation Model: Using company salary history, industry ranges, location, seniority, and public government data, our models predict the salary range for job postings, providing comprehensive human resources (HR) data. • Government Classification Models: We developed models to classify job postings into Standard Occupation Codes (SOC) by the BLS and to categorize companies into industries based on their job posting information, enriching human resources (HR) data. Data Sourcing • Multiple Data Sources: Aggregated from top US job boards, including Indeed (80%), LinkedIn, and company career pages, enhancing human resources (HR), salary, and payroll data. • Advanced Web Scraping: Collects job postings hourly, but AI-LLM enhancements mean LinkedIn data is delivered daily, ensuring quality human resources (HR), salary, and payroll data. • Human-Labeled Annotations: Ensures accurate human resources (HR), salary, and payroll data classification and extraction. • Data Deduplication: Eliminates redundant LinkedIn job postings, ensuring unique human resources (HR), salary, and payroll data. • Continuous Data Validation: Cross-references multiple sources to maintain human resources (HR), salary, and payroll data accuracy and reliability. • Quality Assurance: Dedicated team ensures comprehensive, accurate, and actionable human resources (HR), salary, and payroll data. Primary Use-Cases and Verticals HR Tech: • HR Analytics: Gain insights into industry demands and job market trends with human resources (HR), salary, and payroll data. • HR Strategy: Develop effective HR strategies based on comprehensive human resources (HR) data. • HR Intelligence: Optimize HR practices and improve talent acquisition with LinkedIn human resources (HR), salary, and payroll data. Lead Generation: • Lead Generation: Identify leads and understand hiring needs with LinkedIn human resources (HR), salary, and payroll data. • Account-Based Marketing (ABM): Tailor marketing to specific accounts using human resources (HR), salary, and payroll data. • Lead Data Enrichment: Enhance lead data with detailed LinkedIn human resources (HR), salary, and payroll data. Business Intelligence (BI): • Employment Analytics: Support business decisions with human resources (HR), salary, and payroll data. • Competitive Intelligence: Gain insights from LinkedIn job postings trends. • Competitor Insights: Understand competitors' hiring strategies using human resources (HR), salary, and payroll data. Market Research: • Market Research: Conduct research on labor market dynamics with human resources (HR), salary, and payroll data. • Job Market Pricing: Establish market pricing with LinkedIn salary data. • Job Pricing: Determine competitive salary ranges using human resources (HR), salary, and payroll data. Machine Learning (ML) & Natural Language Processing (NLP): • Machine Learning (ML): Develop models to predict LinkedIn job market trends using human resources (HR) data. • Natural Language Processing (NLP): Extract and analyze LinkedIn job postings data for human resources (HR) insights. Corporate Development: • Corporate Development: Inform strategic initiatives with LinkedIn human resources (HR), salary, and payroll data. • Hiring: Optimize hiring strategies and identify talent opportunities using human resources (HR), salary, and payroll data. Job Boards Listings: • Indeed Data: Gain insights from Indeed job market trends. • LinkedIn Job Posting Data: Understand industry-specific hiring trends with LinkedIn human resources (HR), salary, and payroll data. Integration with Broader Offering • Complementary Data Integration: LinkedIn Job Postings Data and Title & Skill Taxonomy Data integrate with other products, providing a comprehensive view of the job market, skill trends, and industry movements, enhancing human resources (HR), salary, and payroll data. • Enhanced Data Insights: Combining LinkedIn job postings with title & skill taxonomy data offers a multi-dimensional perspective, enabling informed decision-making with human resources (HR), salary, and payroll data. • Scalable Solutions: Suitable for businesses of all sizes, these data products support growth and strategic initiatives using human resources (HR), salary, and payroll data. • Customizable Data Solutions: Tailored to meet specific business needs, LinkedIn job postings and title & skill taxonomy data can be enriched with additional layers, delivering targeted insights for human resources (HR), salary, and payroll data. • Innovative Technology: Leveraging advanced AI & LLM models verified by human experts, these products ensure reliable and accurate human resources (HR), salary, and payroll data. • Versatile Applications: Integration enhances HR analytics, lead generation, competitive intelligence, and market research, providing value across business verticals with human resources (HR), salary, and payroll data. • Continuous Improvement: Ongoing enhancements ensure LinkedIn job postings and title & skill taxonomy data remain valuable within the human resources (HR), salary, and payroll data portfolio. 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