five

Canaria | Salary Data | US | 25M+ Monthly Job Postings & 2 Year Historical | AI-LLM Enhanced Salary Data|薪资数据数据集|就业市场分析数据集

收藏
Datarade2024-06-25 收录
薪资数据
就业市场分析
下载链接:
https://datarade.ai/data-products/canaria-salary-data-us-25m-monthly-job-postings-2-ye-canaria-inc
下载链接
链接失效反馈
资源简介:
Data Uniqueness Human-Verified AI & LLM Models: AI and LLM models are meticulously verified by human experts, ensuring high accuracy in classifying industry, job titles, skills, salaries, and locations. Industry Model: Understands job industry from descriptions and classifies them by NAICS, SOC, and SIC codes. Title Taxonomy Model: Identifies accurate job titles using job descriptions, addressing inaccuracies in free job postings. Skill Taxonomy Model: Determines job skills, both soft and hard, using job descriptions, normalized job titles, and recent industry needs. Salary Estimations: Calculates salary ranges based on previous company salary information, industry range, location, and seniority, even when job postings don't include this information. Zip Code Accuracy: Pinpoints correct zip code, state, city, latitude, and longitude for each job posting. Data Enhancement: The model annotation squad ensures data is meticulously refined for precision and usability. Comprehensive Coverage: The dataset includes over 25M monthly job postings in the US, along with 2 years of historical data, providing a broad and detailed view of the job market, with a particular focus on salary data. Daily Updates: Daily updates ensure salary data is always fresh and relevant, capturing the latest trends and changes in the job market. High-Quality Data Attributes: Data encompasses a wide range of attributes, including job titles, skills, salary information, zip codes, and industry classifications, all refined for precision and usability. Skill & Title Taxonomy: Over 38,000 unique skills and 530,000 unique job titles refined to 53,000+ normalized unique job titles. Improved Zip Code Knowledge: Enhanced accuracy for geographic data. Benefits, Certifications, and Qualifications: Comprehensive details included. Industry-Based Search: SOC, NAICS, and SIC industry-based search with 867 unique SOC codes. Remote, Hybrid, or Onsite Knowledge: Detailed job location information. Deduplicated Job Postings: Ensures the highest quality by removing duplicates. Versatile Applications: Ideal for HR Tech, Lead Generation, and Investors, offering actionable insights and supporting strategic decision-making across various sectors. Data Sourcing Multiple Data Sources: Data is aggregated from top US job boards, including Indeed (approximately 80%), LinkedIn, other leading job posting websites, and company career pages. Advanced Web Scraping: Advanced web scraping techniques are utilized to collect job postings hourly. However, enhancing the data with AI-LLM models takes time, so salary data is delivered daily to ensure high-quality results. Human-Labeled Annotations: AI & LLM models are trained and verified with human-labeled annotations to ensure the highest accuracy in data classification and attribute extraction. Data Deduplication: Rigorous data deduplication processes are implemented to eliminate redundant job postings, ensuring the uniqueness and quality of the data. Continuous Data Validation: Data undergoes continuous validation processes, including cross-referencing with multiple sources, to maintain accuracy and reliability. Quality Assurance: A dedicated team is responsible for ongoing quality assurance, ensuring the data remains comprehensive, accurate, and actionable for clients. Primary Use-Cases and Verticals of the Data Product: HR Tech: HR Analytics: Gain insights into industry demands, salary benchmarks, and job market trends to support strategic HR decisions. HR Strategy: Develop and implement effective HR strategies based on comprehensive salary data. HR Intelligence: Analyze job market salary data to optimize HR practices and improve talent acquisition. Lead Generation: Lead Generation: Utilize salary data to identify potential leads and understand the hiring needs of prospective clients. Account-Based Marketing (ABM): Tailor marketing efforts to specific accounts based on salary data trends. Lead Data Enrichment: Enhance lead data with detailed job market salary information. Business Intelligence (BI): Employment Analytics: Analyze job market trends and employment data to support business decisions. Competitive Intelligence: Compare salary data trends across different companies and industries to gain competitive insights. Competitor Insights: Understand competitors' hiring activities and strategies. Market Research: Market Research: Conduct research on labor market dynamics, employment trends, and skill demand. Job Market Pricing: Analyze salary data to establish market pricing for various roles. Job Pricing: Determine competitive salary ranges for job postings based on comprehensive data analysis. Machine Learning (ML) & Natural Language Processing (NLP): Machine Learning (ML): Develop ML models to predict job market salary trends and enhance job matching algorithms. Natural Language Processing (NLP): Utilize NLP techniques to extract and analyze salary data for improved insights. Corporate Development: Corporate Development: Inform strategic initiatives and business growth plans with detailed salary data. Hiring: Optimize hiring strategies and identify talent acquisition opportunities. Job Boards Listings: Indeed Data: Leverage data from Indeed to gain insights into job market trends and hiring practices. Job Posting Data: Utilize job postings data to understand industry-specific hiring trends. Integration with Broader Offering Complementary Data Integration: Salary Data and Title & Skill Taxonomy Data seamlessly integrate with each other and other data products offered by Canaria Inc. This integration provides a comprehensive view of the job market, skill trends, and industry movements. Enhanced Data Insights: By combining salary data with title & skill taxonomy data, users gain a multi-dimensional perspective on job market dynamics, workforce trends, and required skills. This holistic approach enables more informed decision-making across various business functions. Scalable Solutions: These data products are part of a scalable suite of solutions catering to businesses of all sizes. Whether for small businesses or large enterprises, clients can leverage these datasets alongside other offerings to support growth and strategic initiatives. Customizable Data Solutions: Canaria Inc. provides tailored data solutions that can be customized to meet specific business needs. Salary data and title & skill taxonomy data can be enriched with additional data layers, such as demographic information or economic indicators, to deliver targeted insights. Innovative Technology: Utilizing advanced AI & LLM models verified by human experts, these data products exemplify Canaria Inc.'s commitment to leveraging cutting-edge technology to deliver high-quality, actionable data. This approach ensures reliability and accuracy across all Canaria Inc. data offerings. Versatile Applications: The integration of salary data with title & skill taxonomy data enhances a wide range of applications, from HR analytics and lead generation to competitive intelligence and market research. This versatility is a hallmark of Canaria Inc.'s broader data offering, designed to provide value across multiple business verticals. Continuous Improvement: As part of a broader commitment to excellence, Canaria Inc. continuously enhances its data products. Both salary data and title & skill taxonomy data benefit from ongoing model improvements, frequent updates, and user feedback, ensuring they remain valuable assets within the overall data portfolio.
提供机构:
Canaria Inc.
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4098个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

CHARLS

中国健康与养老追踪调查(CHARLS)数据集,旨在收集反映中国45岁及以上中老年人家庭和个人的高质量微观数据,用以分析人口老龄化问题,内容包括健康状况、经济状况、家庭结构和社会支持等。

charls.pku.edu.cn 收录

YOLO Drone Detection Dataset

为了促进无人机检测模型的开发和评估,我们引入了一个新颖且全面的数据集,专门为训练和测试无人机检测算法而设计。该数据集来源于Kaggle上的公开数据集,包含在各种环境和摄像机视角下捕获的多样化的带注释图像。数据集包括无人机实例以及其他常见对象,以实现强大的检测和分类。

github 收录

历史航班准点率

航班在最近30天里准点程度的参数综合,反映了该航班可能延误的概率指数。具体计算方法:在最近30天内,航班降落时间比计划降落时间(航班时刻表上的时间)延迟半小时以上或航班取消的情况称为延误,将出现延误情况的航班数量除以30天内实际执飞的航班数量得出延误率,准点率=1-延误率。每日全面更新一次。

苏州大数据交易所 收录

UAVDT

UAVDT数据集由中国科学院大学等机构创建,包含约80,000帧从10小时无人机拍摄视频中精选的图像,覆盖多种复杂城市环境。数据集主要关注车辆目标,每帧均标注了边界框及多达14种属性,如天气条件、飞行高度、相机视角等。该数据集旨在推动无人机视觉技术在不受限制场景下的研究,解决高密度、小目标、相机运动等挑战,适用于物体检测、单目标跟踪和多目标跟踪等基础视觉任务。

arXiv 收录

VisDrone2019

VisDrone2019数据集由AISKYEYE团队在天津大学机器学习和数据挖掘实验室收集,包含288个视频片段共261,908帧和10,209张静态图像。数据集覆盖了中国14个不同城市的城市和乡村环境,包括行人、车辆、自行车等多种目标,以及稀疏和拥挤场景。数据集使用不同型号的无人机在各种天气和光照条件下收集,手动标注了超过260万个目标边界框,并提供了场景可见性、对象类别和遮挡等重要属性。

github 收录