Glassdoor Data for U.S. Salary Intelligence, Executive Compensation & HR Strategy Glassdoor Data is one of the most actionable and trusted sources of alternative data for understanding salary benchmarks, executive compensation, and company-level payroll dynamics. This Glassdoor Data product provides granular salary insights across thousands of U.S. companies, based directly on job titles, experience levels, and compensation submissions. Each record includes: • Company name • Job title • Location • Years of experience • Submission count • Total pay • Base and additional pay • Scrape timestamp • Source URL The dataset is designed to offer transparent, real-world compensation intelligence for roles across industries and seniority levels—without relying on external company datasets or third-party matching. Whether you're benchmarking pay levels, building compensation bands, or modeling payroll scenarios, this Glassdoor salary data delivers raw, high-signal insights to support strategic decisions across HR, finance, and analytics teams. This dataset is ideal for compensation strategists, HR teams, financial analysts, and market researchers who require consistent, transparent, and scalable compensation intelligence to support pay benchmarking, cost modeling, or workforce evaluation. Use Cases: What Problems This Glassdoor Data Solves Whether you’re building a salary model, evaluating leadership compensation trends, or enhancing your payroll benchmarking strategy, Canaria’s Glassdoor data replaces assumptions with structured, evidence-based insights. Compensation Benchmarking & Strategy • Benchmark average salary ranges, executive pay, and bonus structures by industry • Understand pay differences by company size, structure, and market positioning • Compare compensation levels across roles, sectors, and seniority levels • Support equitable pay band development and validate DEI-focused compensation initiatives • Track salary progression over time across different industries and geographies Financial Intelligence & Valuation Modeling • Integrate salary and payroll data into operating cost and DCF models • Analyze compensation-to-revenue ratios across public and private companies • Use Glassdoor executive compensation signals to estimate fiscal discipline and growth maturity • Evaluate total labor cost benchmarks across sectors to support investment or M&A models • Support startup valuation modeling using real-world salary and review signals HR Analytics & Payroll Planning • Calibrate compensation plans, equity offers, and incentive structures based on real benchmarks • Align workforce planning with external salary and benefits trends • Compare employee sentiment with compensation ratings to monitor retention risk • Understand compensation differentials across company size brackets and industries • Evaluate which employers attract and retain talent based on pay satisfaction reviews Company Analysis & Leadership Signals • Track CEO and leadership pay benchmarks to evaluate executive strategy alignment • Use Glassdoor scores and review counts to evaluate employee morale and culture • Analyze patterns in rating trends, review frequency, and compensation satisfaction • Compare compensation strategies across different growth stages and business models • Detect early warning signals through declining ratings or increasing negative reviews Who Uses Canaria’s Glassdoor Data? • HR & People Analytics teams refining salary structures • Finance and Operations teams modeling payroll scenarios • Private Equity, VC, and Corporate Strategy teams estimating workforce cost risk • Compensation Consultants benchmarking roles by industry and geography • BI and Research Analysts tracking labor cost trends and employer sentiment • KYC and corporate due diligence workflows integrating public employee reviews Summary Canaria’s Glassdoor Data product delivers verified, structured, and independently sourced salary and compensation intelligence for U.S. companies. With a focus on executive pay, workforce sentiment, and real-world salary benchmarks, it equips HR, finance, and strategy teams with the tools needed to model, analyze, and optimize compensation decisions.

From benchmarking CEO pay to understanding employee satisfaction and cost structures, this dataset supports decision-making across compensation strategy, HR planning, and company evaluation—at scale.

About Canaria Inc. Canaria Inc. is a leader in alternative data, specializing in job market intelligence, LinkedIn company data, Glassdoor salary analytics, and Google Maps location insights. We deliver clean, structured, and enriched datasets at scale using proprietary data scraping pipelines and advanced AI/LLM-based modeling, all backed by human validation. Our platform also includes Google Maps data, providing verified business location intelligence — such as addresses, coordinates, hours, categories, and ratings — which is fully matchable with our company datasets for powerful ...

This data file contains a list of public sector executives, organized by Sector and Employer, whose employers are required to disclose their total compensation each year in accordance with the Public Sector Employers Act if they receive an annualized base salary of $125,000 or more and are one of the top five decision makers for the employer. The file lists base salary and total compensation for the Reporting Year. For more details please refer to the individual disclosure statements.

Abstract This paper verifies the evolution of the remuneration pattern of different higher-level careers within the Brazilian federal executive branch from 1998 to 2015. In recent years, the differences in remuneration have substantially increased in the Brazilian civil service. However, the results obtained through cluster analysis suggest a pattern of greater pay raise for “typical state careers” to the detriment of others. This reveals a pattern of salary appreciation within the executive branch and, especially, an internal distributive conflict, in which those careers closer to the central power and with characteristics of “typical state careers” were gradually benefiting, establishing a major change in the relative remuneration pattern among different careers over the studied period.

Explore surprising shifts in startup executive pay: VPs see up to 26% cash increases while equity drops 31%. New compensation data reveals changing venture trends.

This data file contains a list of public sector executives, organized by Sector and Employer, whose employers are required to disclose their total compensation each year in accordance with the Public Sector Employers Act if they receive an annualized base salary of $125,000 or more and are one of the top five decision makers for the employer. The file lists base salary and total compensation for the Reporting Year. For more details please refer to the individual disclosure statements.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for executive management in the U.S.

Discover the booming Employee Salary and Benefits Strategy market! Learn about its projected $85 billion value by 2033, key drivers like regulatory compliance and tech adoption, and top players shaping this dynamic sector. Get insights into regional trends and growth forecasts.

ABSTRACT Objective: in order to produce new insights for the knowledge about the effects of executive compensation on companies, relationship between performance (short-term) and investment policy (long-term) in Brazilian family and non-family companies listed in Brazil, Bolsa, Balcão (B3) are investigated. Methods: documentary procedure research was conducted with data from Economática® and company reports (Management Report, Reference Form and Explanatory Notes). The sample of 87 companies consists of 48 family and 39 non-family companies. Results: indicate that the short-term variable remuneration is related to the performance and investment policy of the companies, while the long-term variable remuneration was not significant. Short-term variable compensation reveals potential to maximize corporate performance, with a stronger impact on non-family companies. In view of the investment policy, short-term variable compensation presents a negative relation, but this effect is reverted to non-family companies. Conclusion: executive compensation can be a governance mechanism to align the interests of the parties, both in family and non-family companies. However, its precise dimensioning must consider the type of ownership and corporate management.

The Executive Compensation Advisory market is an integral component of corporate governance that focuses on structuring competitive and equitable compensation packages for top-tier executives. This market encompasses a range of services, including salary benchmarking, incentive design, compliance with regulatory req

AI Job Market & Salary Analysis 2025 Dataset

Dataset Overview

This comprehensive dataset contains detailed information about AI and machine learning job positions, salaries, and market trends across different countries, experience levels, and company sizes. Perfect for data science enthusiasts, career researchers, and market analysts for practice purposes.

Dataset Title

Global AI Job Market & Salary Trends 2025: Complete Analysis of 15,000+ Positions

Dataset Description

What's Inside

It includes detailed salary information, job requirements, company insights, and geographic trends.

Key Features: - 15,000+ job listings from 50+ countries - Salary data in multiple currencies (normalized to USD) - Experience level categorization (Entry, Mid, Senior, Executive) - Company size impact analysis - Remote work trends and patterns - Skills demand analysis - Geographic salary variations - Time-series data showing market evolution

Columns Description

Potential Use Cases

1. Salary Prediction Models

   • Build ML models to predict AI job salaries
   • Analyze factors affecting compensation
   • Compare salaries across different locations

2. Market Trend Analysis

   • Track the evolution of AI job market
   • Identify emerging job roles and skills
   • Analyze remote work adoption patterns

3. Career Planning

   • Understand skill requirements for different positions
   • Compare opportunities across countries
   • Plan career progression paths

4. Business Intelligence

   • Company hiring patterns analysis
   • Skills gap identification
   • Market competition insights

5. Geographic Studies

   • Cost of living vs. salary analysis
   • Regional market maturity assessment
   • Immigration pattern correlations

Data Collection Methodology

This is a synthetic dataset created for educational purposes to simulate AI job market patterns. All data is algorithmically generated based on industry research and market trends.

Sample Data Preview

job_id,job_title,salary_usd,experience_level,company_location,remote_ratio
AI001,Senior ML Engineer,145000,SE,United States,50
AI002,Data Scientist,89000,MI,Germany,100
AI003,AI Research Scientist,175000,EX,United Kingdom,0

Kaggle Dataset Tags

#artificial-intelligence #machine-learning #jobs #salary #career #data-science #employment #tech-industry #remote-work #compensation

Dataset Files Structure

ai-job-market-2025/
├── main_dataset.csv (15,247 rows)
├── skills_analysis.csv (skill frequency data)
├── company_profiles.csv (company information)
├── geographic_data.csv (country/city details)
├── time_series.csv (monthly trends)
└── data_dictionary.pdf (detailed documentation)

Acknowledgments

All personal information has been anonymized. This dataset is intended for educational and research purposes.

Discussion Topics for Community Engagement

1. What factors most influence AI job salaries in your analysis?
2. Interesting patterns you've discovered in remote work trends
3. Best visualization techniques for this type of employment data
4. Prediction model results - share your accuracy scores!
5. Geographic insights that surprised you

Suggested Notebook Titles for Analysis

• Predicting AI Salaries: A Complete ML Pipeline
• The Great Remote Work Shift in AI Jobs
• Skills That Pay: What Makes AI Engineers Valuable
• Global AI Talent Migration Patterns
• Company Size vs. Compensation: The AI Edition

*This dat...

This report was written in collaboration between the Mayor's Office of Innovation and the Rochester Monroe Anti-Poverty Initiative (RMAPI), and released in July 2017. Executive SummaryThe purpose of this report is to explore the demographic and earning disparities in the local workforce in Monroe County. It focuses on people who live in poverty, despite being employed, and aims to help the community better understand major contributing factors preventing residents from becoming self-sufficient. It is meant to augment and contextualize existing data on the state of poverty in Rocheser and to inform the strategy deployed by the Rochester Monroe Anti-Poverty Initiative.This report includes analysis on the correlations between the industries in which Rochester residents in poverty are employed, the wages they earn, and the hours that they work. It also examines these factors by race, gender, educational attainment, and physical ability. Through the analysis of several data sources, inlcuding the U.S. Census Public Use Microdata Sample, the Office of Innovation examines how the intersection of these factors contributes to Rochester's poverty landscape. Key findings outlined in this report include:• Many part-time and seasonal workers live in poverty or are not self sufficient.• Minorities are over-represented in several key service industries.• The industries with over-representation of minorities also tend to be the county’s lowest paying and largest sectors.• Minorities earn less than their white counterparts in nearly every industry sector.• Regardless of educational attainment, the wage gap between whites and minorities persists.The report concludes that wages play a key role in preventing minorities, women, and the disabled from achieving self-sufficiency in Rochester. The recommended next steps for RMAPI are to engage employers and lawmakers in the industry sectors where minorities are both underpaid and over-representated and work towards increasing wages to help meet the goal of increasing self-sufficiency and reducing poverty in Rochester by 50% over the next 15 years.Data Source:2015 Census American Community Survey 5-Year Estimates, Public Microdata SampleData and documentation can be accessed here:https://www.census.gov/programs-surveys/acs/data/pums.html

Ofcom publishes the salary details of its Board and Executive Committee. In addition to the individuals named in the Annual Report, there are several individuals whose salaries were greater than £150,000. This report lists those individuals.

This study examined whether CEOs’ narcissistic tendencies prompt them to manipulate earnings to achieve the earnings threshold. On the basis of existing literature (Marquez-Illescas et al., 2018; Olsen et al., 2013), this study used a four-item index to construct the rating system for CEO narcissism ( ): (a) the prominence of the CEO’s photograph in annual reports, (b) the prominence of the CEO’s photograph in corporate social responsibility (CSR) reports, (c) the CEO’s cash compensation, and (d) the noncash compensation of the CEO relative to other top executives at the same company. Our rating system incorporated CEOs that appear in photographs in annual and CSR reports. CSR reports follow widely adopted global guidelines set by the Global Reporting Initiative for the transparent disclosure of corporate values and performances, whereby the CSR report constitutes voluntary information disclosure (Krishnamurti et al., 2018).

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for executive master of business administration in the U.S.

This large dataset contains job descriptions and rankings among various criteria such as work-life balance, income, culture, etc. The data covers the various industries in the UK. Great dataset for multidimensional sentiment analysis.

This data set complements the Glassdoor dataset located [here].(https://www.kaggle.com/datasets/davidgauthier/glassdoor-job-reviews-2)

Please cite as: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=FQstpaoAAAAJ&citation_for_view=FQstpaoAAAAJ:UebtZRa9Y70C

Glassdoor Reviews

Glassdoor produces reports based upon the data collected from its users, on topics including work–life balance, CEO pay ratios, lists of the best office places and cultures, and the accuracy of corporate job searching maxims. Data from Glassdoor has also been used by outside sources to produce estimates on the effects of salary trends and changes on corporate revenues. Glassdoor also puts the conclusions of its research of other companies towards its own company policies. In 2015, Tom Lakin produced the first study of Glassdoor in the United Kingdom, concluding that Glassdoor is regarded by users as a more trustworthy source of information than career guides or official company documents.

Features

The columns correspond to the date of the review, the job name, the job location, the status of the reviewers, and the reviews. Reviews are divided in s sub-categories Career Opportunities, Comp & Benefits, Culture & Values, Senior Management, and Work/Life Balance. In addition, employees can add recommendations on the firm, the CEO, and the outlook.

Other information

Ranking for the recommendation of the firm, CEO approval, and outlook are allocated categories v, r, x, and o, with the following meanings: v - Positive, r - Mild, x - Negative, o - No opinion

Some examples of the textual data entries

MCDONALD-S I don't like working here,don't work here Headline: I don't like working here,don't work here Pros: Some people are nice,some free food,some of the managers are nice about 95% of the time Cons: 95% of people are mean to employees/customers,its not a clean place,people barely clean their hands of what i see,managers are mean,i got a stress rash because of this i can't get rid of it,they don't give me a little raise even though i do alot of crap there for them Rating: 1.0

KPMG Quit working people to death Headline: Quit working people to death Pros: Lots of PTO, Good company training Cons: long hours, clear disconnect between management and staff, as corporate as it gets Rating: 2.0

PRIMARK Sales assistant Headline: Sales assistant Pros: Lovely staff, managers are also very nice Cons: Hardwork, often rude customers, underpaid for u18 Rating: 3.0

J-P-MORGAN Life in JPM, Bangalore Headline: Life in JPM, Bangalore Pros: Good place to start, lots of opportunity. Cons: Be ready to put in a lot of efforts not a place to chill out. Rating: 4.0

VODAFONE Good to be here Headline: Good to be here Pros: Fast moving with technology. Leading Cons: There are areas you may want to avoid Rating: 5.0

This study utilizes data from A-share listed companies between 2011 and 2020 to empirically investigate the impact and mechanism of public welfare donations on the internal income gap of enterprises. The research findings indicate that public welfare donations significantly increase the per capita salary of management, while their impact on the per capita salary of ordinary employees is not significant, thus leading to an expansion of the internal income gap within enterprises. The results from mechanism testing reveal that the income tax benefits resulting from charitable donations and the rise in corporate operating income have contributed to an increase in excess rent shared by enterprises and employees. Due to a stronger bargaining power, management shares more excess rents, thereby widening the income gap within the enterprise. Heterogeneity analysis demonstrates that public welfare donations have a greater impact on the internal income gap of non-state-owned enterprises; however, limiting executive compensation and enhancing employees’ bargaining power can mitigate this widening effect caused by public welfare donations on enterprise’s internal income gap. The research value of this study is threefold. Firstly, there is a scarcity of studies on the impact of public welfare donations on the income gap within enterprises, and this study contributes to enriching the research in this area. Secondly, this paper examines the effect of tax incentives for public welfare donations on the internal income gap of enterprises, thereby deepening the research on the impact of tax reduction and fee reduction, as well as expanding our understanding of corporate income tax preferential policies. Thirdly, it offers insights into improving enterprise compensation systems and enhancing corporate governance. Senior executives can potentially allocate more excess rent through their strong bargaining power. If their compensation remains unrestricted, it may lead to a widening internal income gap and negatively affect company operational efficiency.

New data reveals post-Series A founder CEOs taking 24% less salary but 32% more equity. Analysis of 800 startups shows shifting compensation trends in venture-backed companies.

This paper aims to examine the impact of executive compensation incentive on corporate innovation capability by dividing executive compensation incentive into short-term monetary incentive and long-term equity incentive. We also investigate the interaction between the two types of executive compensation incentive. Data are collected from China’s agro-based companies during 2012–2019, and multiple regression analysis is utilized. The empirical results show that short-term monetary incentive has no impact on innovation capability, while long-term equity incentive stimulates innovation capability. Regarding company ownership, the impact of long-term equity incentive in state-owned enterprises is greater than that in private-owned enterprises. In addition, the complementary effect between short-term and long-term compensation incentive has a positive impact on innovation capability regardless of company ownership. The findings of this paper could help agribusiness managers to design the reasonable incentive system to incentivize corporate executives and enhance the capability of independent innovation.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for mba information technology leadership executive in the U.S.