100+ datasets found
  1. Highest paying bachelor's degrees in the U.S. 2021/22, by mid-career pay

    • statista.com
    • ai-chatbox.pro
    Updated Jul 5, 2024
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    Statista (2024). Highest paying bachelor's degrees in the U.S. 2021/22, by mid-career pay [Dataset]. https://www.statista.com/statistics/633793/highest-paying-bachelor-degrees-in-the-us/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    United States
    Description

    This statistic shows the leading bachelor's degrees with the highest mid-career salary in the U.S. in the academic year 2020/21. In 2020/21, petroleum engineering was ranked first with the mid-career salary of 182,000 U.S. dollars.

  2. U.S. median annual wage 2023, by major occupational group

    • statista.com
    Updated Aug 27, 2024
    + more versions
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    Statista (2024). U.S. median annual wage 2023, by major occupational group [Dataset]. https://www.statista.com/statistics/218235/median-annual-wage-in-the-us-by-major-occupational-groups/
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    Dataset updated
    Aug 27, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2023
    Area covered
    United States
    Description

    As of 2023, the median wage for employees in healthcare support occupations was about 36,140 U.S. dollars. The occupational group with the highest annual median wage was management occupations. Mean wages for the same occupational groups can be accessed here.

  3. Salary Datasets

    • brightdata.com
    .json, .csv, .xlsx
    Updated Jan 8, 2025
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    Bright Data (2025). Salary Datasets [Dataset]. https://brightdata.com/products/datasets/salary
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    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    Jan 8, 2025
    Dataset authored and provided by
    Bright Datahttps://brightdata.com/
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    Unlock valuable salary insights with our comprehensive Salary Dataset, designed for businesses, recruiters, and job seekers to analyze compensation trends, workforce planning, and market competitiveness.

    Dataset Features

    Job Listings & Salaries: Access structured salary data from top job platforms, including job titles, company names, locations, salary ranges, and compensation types. Employer & Industry Insights: Extract company-specific salary trends, industry benchmarks, and hiring patterns. Geographic Pay Disparities: Compare salaries across different regions, cities, and countries to identify location-based compensation trends. Job Market Trends: Monitor salary fluctuations, demand for specific roles, and hiring trends over time.

    Customizable Subsets for Specific Needs Our Salary Dataset is fully customizable, allowing you to filter data based on job titles, industries, locations, experience levels, and salary ranges. Whether you need broad market insights or focused data for recruitment strategy, we tailor the dataset to your needs.

    Popular Use Cases

    Workforce Planning & Talent Acquisition: Optimize hiring strategies by analyzing salary benchmarks and compensation trends. Market Research & Competitive Intelligence: Compare salaries across industries and competitors to stay ahead in talent acquisition. Career Decision-Making: Help job seekers evaluate salary expectations and identify high-paying opportunities. AI & Predictive Analytics: Use structured salary data to train AI models for job market forecasting and compensation analysis. Geographic Expansion & Business Strategy: Assess salary variations across regions to plan business expansions and remote workforce strategies.

    Whether you're optimizing recruitment, analyzing salary trends, or making data-driven career decisions, our Salary Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

  4. Employee wages by occupation, annual

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Jan 24, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Employee wages by occupation, annual [Dataset]. http://doi.org/10.25318/1410041701-eng
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    Dataset updated
    Jan 24, 2025
    Dataset provided by
    Government of Canadahttp://www.gg.ca/
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Average hourly and weekly wage rate, and median hourly and weekly wage rate by National Occupational Classification (NOC), type of work, gender, and age group.

  5. U.S. highest paying occupations 2023

    • statista.com
    Updated Jul 5, 2024
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    Statista (2024). U.S. highest paying occupations 2023 [Dataset]. https://www.statista.com/statistics/243861/highest-paying-occupations-in-the-us/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2023
    Area covered
    United States
    Description

    In 2023, many of the highest paying jobs were those in the medical field. The mean annual pay for psychiatrists was at 256,930 U.S. dollars in the United States. The highest paying occupation was pediatric surgeon, with a mean annual wage of 449,320 U.S. dollars.

  6. G

    Employment income statistics by occupation, major field of study and highest...

    • open.canada.ca
    • www150.statcan.gc.ca
    • +1more
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Employment income statistics by occupation, major field of study and highest level of education: Canada [Dataset]. https://open.canada.ca/data/dataset/b1ab3b82-61ac-49f7-a00a-6b3a64ee7354
    Explore at:
    html, csv, xmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada
    Description

    Detailed labour market outcomes by educational characteristics, including detailed occupation, hours and weeks worked and employment income.

  7. o

    Taiwan 104.com jobs search JD

    • opendatabay.com
    .undefined
    Updated Jun 26, 2025
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    The citation is currently not available for this dataset.
    Explore at:
    .undefinedAvailable download formats
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Datasimple
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Taiwan, Data Science and Analytics
    Description

    Dataset Overview The dataset consists of 26,000 job listings, extracted from a Taiwanese job search platform, focusing on software-related careers. Each listing is detailed with various attributes, providing a comprehensive view of the job market in this sector. Here's a breakdown of the dataset columns:

    職缺類別 (Job Category) 職位類別 (Position Category) 職位 (Position) 縣市 (City/County) 地區 (District/Area) 供需人數 (應徵人數) (Number of Applicants) 公司名稱 (Company Name) 職缺名稱 (Job Title) 工作內容 (Job Description) 職務類別 (Job Type) 工作待遇 (Salary) 工作性質 (Nature of Work) 上班地點 (Work Location) 管理責任 (Management Responsibility) 上班時段 (Working Hours) 需求人數 (Number of Positions) 工作經歷 (Work Experience) 學歷要求 (Educational Requirements) 科系要求 (Departmental Requirements) 擅長工具 (Tools Proficiency) 工作技能 (Job Skills) 其他條件 (Other Conditions) 資本額 (Capital Amount) 員工人數 (Number of Employees) 公司標籤 (Company Tags) Analytical Insights Exploratory Data Analysis Perform exploratory data analysis using libraries like Pandas and NumPy. Examine trends in job categories, salaries, and educational requirements. Analyze the distribution of jobs across different cities and districts. Visualization Create visual representations of the dataset using Python visualization libraries. Plot job distribution across various sectors or locations. Visualize salary ranges and compare them with educational and experience requirements. Practice with SQL or Pandas Queries Utilize the dataset to refine SQL query skills or Pandas data manipulation techniques. Execute queries to extract specific information, such as the most in-demand skills or the companies offering the highest salaries. NLP Analysis and Tasks for Software Jobs Dataset This dataset, encompassing 26,000 job listings from the Taiwanese software industry, is ripe for a variety of Natural Language Processing (NLP) analyses. Below are some recommended NLP tasks and analyses that can be conducted on this dataset.

    Text Classification Job Category Prediction: Train a classification model to predict the job category (職缺類別) using job descriptions (工作內容). Salary Range Classification: Classify jobs into different salary brackets based on their descriptions and titles, helping to identify features associated with higher salaries. Sentiment Analysis Company Reputation Analysis: Analyze the sentiment of company tags (公司標籤) to assess the general sentiment or reputation of companies listed in the dataset. Topic Modeling Identifying Key Job Requirements: Apply LDA (Latent Dirichlet Allocation) to job descriptions for uncovering common themes or required skills in the software sector. Named Entity Recognition (NER) Information Extraction: Implement NER to extract specific entities like tools (擅長工具), skills (工作技能), and educational qualifications (學歷要求) from job descriptions. Text Summarization Summarizing Job Descriptions: Develop algorithms for generating concise summaries of job descriptions, enabling quick understanding of key points. Language Modeling Job Description Generation: Use language models to create realistic job descriptions based on input prompts, assisting in job listing creation or understanding industry language trends. Machine Translation (If Applicable) Dataset Translation for Global Accessibility: Translate the dataset content into English or other languages for international accessibility, using machine translation models. Predictive Analysis Predicting Applicant Volume: Use historical data to forecast the number of applicants (供需人數 (應徵人數)) a job listing might attract based on various factors. By leveraging these NLP techniques, insightful findings can be extracted from the dataset, beneficial for both job seekers and employers in the software field. This dataset offers a practical opportunity to apply NLP skills in a real-world setting.

    License

    CC0

    Original Data Source: Taiwan 104.com jobs search JD

  8. d

    Title and Salary Listing

    • catalog.data.gov
    • datasets.ai
    • +5more
    Updated Apr 12, 2025
    + more versions
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    State of New York (2025). Title and Salary Listing [Dataset]. https://catalog.data.gov/dataset/title-and-salary-listing
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    Dataset updated
    Apr 12, 2025
    Dataset provided by
    State of New York
    Description

    The Title and Salary Listing is a compilation of job titles under the jurisdiction of the Department of Civil Service.

  9. C

    Current Employee Names, Salaries, and Position Titles

    • chicago.gov
    • data.cityofchicago.org
    • +4more
    application/rdfxml +5
    Updated Jun 26, 2025
    + more versions
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    City of Chicago (2025). Current Employee Names, Salaries, and Position Titles [Dataset]. https://www.chicago.gov/city/en/depts/dhr/dataset/current_employeenamessalariesandpositiontitles.html
    Explore at:
    json, csv, tsv, application/rssxml, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    City of Chicago
    Description

    This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html

    Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)

  10. Estimates of earnings for the highest paid employee jobs by public and...

    • cy.ons.gov.uk
    • ons.gov.uk
    zip
    Updated Nov 1, 2024
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    Office for National Statistics (2024). Estimates of earnings for the highest paid employee jobs by public and private sectors, UK [Dataset]. https://cy.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/estimatesofearningsforthehighestpaidemployeejobsbypublicandprivatesectorsuk
    Explore at:
    zipAvailable download formats
    Dataset updated
    Nov 1, 2024
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Estimates of paid hours worked, weekly, hourly and annual earnings for the highest paid (90 to 99 percentiles) employee jobs in the UK, by public and private sectors.

  11. 🎓 US Graduates

    • kaggle.com
    Updated Aug 14, 2023
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    mexwell (2023). 🎓 US Graduates [Dataset]. https://www.kaggle.com/datasets/mexwell/us-graduates/discussion?sort=undefined
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 14, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    mexwell
    License

    http://www.gnu.org/licenses/old-licenses/gpl-2.0.en.htmlhttp://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html

    Area covered
    United States
    Description

    The data in this library comes from the National Survey of Recent College Graduates. Included is information about employment numbers, major information, and the earnings of different majors. Many majors were not available before 2010, so their values have been recorded as 0 (note that this may affect the averages shown in the bar charts).

    Data Dictionary

    KeyList of...CommentExample Value
    YearIntegerThe year that this report was made for.1993
    Demographics.TotalIntegerThe estimated number of people awarded degrees in this major during this year.1295598
    Education.MajorStringThe name of the major for these graduated students."Biological Sciences"
    Salaries.HighestFloatThe highest recorded salary reported for employed people with this degree during this year.999999.0
    Salaries.LowestFloatThe lowest recorded salary reported for employed people with this degree during this year.0.0
    Salaries.MeanFloatThe average (mean) recorded salary reported for employed people with this degree during this year.160585.73
    Salaries.MedianFloatThe median recorded salary reported for employed people with this degree during this year.51000.0
    Salaries.QuantityIntegerThe number of salaries reported for employed people with this degree during this year.13432
    Salaries.Standard DeviationFloatThe standard deviation (which gives the amount of variance) of salaries reported for employed people with this degree during this year.297818.25
    Demographics.Ethnicity.AsiansIntegerThe estimated number of people identifying as Asian that were awarded degrees in this major during this year.84495
    Demographics.Ethnicity.MinoritiesIntegerThe estimated number of people identifying as a minority (e.g., Black, African American, Native American) that were awarded degrees in this major during this year.115016
    Demographics.Ethnicity.WhitesIntegerThe estimated number of people identifying as White that were awarded degrees in this major during this year.1094775
    Demographics.Gender.FemalesIntegerThe estimated number of women awarded degrees in this major during this year.551695
    Demographics.Gender.MalesIntegerThe estimated number of women awarded degrees in this major during this year.743903
    Education.Degrees.BachelorsIntegerThe estimated number of bachelor degrees awarded in this for major during this year.671374
    Education.Degrees.DoctoratesIntegerThe estimated number of doctoral degrees awarded in this for major during this year.90543
    Education.Degrees.MastersIntegerThe estimated number of Masters awarded in this for major during this year.248813
    Education.Degrees.ProfessionalsIntegerThe estimated number of professional degrees awarded in this for major during this year.284869
    Employment.Employer Type.Business/IndustryIntegerThe number of people with a degree in this major during this year who described their Employer Type as "Business/Industry".669270
    Employment.Employer Type.Educational InstitutionIntegerThe number of people with a degree in this major during this year who described their Employer Type as an "Educational Institution".300468
    Employment.Employer Type.GovernmentIntegerThe number of people with a degree in this major during this year wh...

  12. Wages

    • open.canada.ca
    • ouvert.canada.ca
    csv
    Updated Dec 12, 2024
    + more versions
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    Employment and Social Development Canada (2024). Wages [Dataset]. https://open.canada.ca/data/en/dataset/adad580f-76b0-4502-bd05-20c125de9116
    Explore at:
    csvAvailable download formats
    Dataset updated
    Dec 12, 2024
    Dataset provided by
    Ministry of Employment and Social Development of Canadahttp://esdc-edsc.gc.ca/
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    The wages on the Job Bank website are specific to an occupation and provide information on the earnings of workers at the regional level. Wages for most occupations are also provided at the national and provincial level. In Canada, all jobs are associated with one specific occupational grouping which is determined by the National Occupational Classification. For most occupations, a minimum, median and maximum wage estimates are displayed. They are update annually. If you have comments or questions regarding the wage information, please contact the Labour Market Information Division at: NC-LMI-IMT-GD@hrsdc-rhdcc.gc.ca

  13. d

    Job Postings Dataset for Labour Market Research and Insights

    • datarade.ai
    Updated Sep 20, 2023
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    Oxylabs (2023). Job Postings Dataset for Labour Market Research and Insights [Dataset]. https://datarade.ai/data-products/job-postings-dataset-for-labour-market-research-and-insights-oxylabs
    Explore at:
    .json, .xml, .csv, .xlsAvailable download formats
    Dataset updated
    Sep 20, 2023
    Dataset authored and provided by
    Oxylabs
    Area covered
    British Indian Ocean Territory, Kyrgyzstan, Zambia, Luxembourg, Jamaica, Anguilla, Switzerland, Tajikistan, Togo, Sierra Leone
    Description

    Introducing Job Posting Datasets: Uncover labor market insights!

    Elevate your recruitment strategies, forecast future labor industry trends, and unearth investment opportunities with Job Posting Datasets.

    Job Posting Datasets Source:

    1. Indeed: Access datasets from Indeed, a leading employment website known for its comprehensive job listings.

    2. Glassdoor: Receive ready-to-use employee reviews, salary ranges, and job openings from Glassdoor.

    3. StackShare: Access StackShare datasets to make data-driven technology decisions.

    Job Posting Datasets provide meticulously acquired and parsed data, freeing you to focus on analysis. You'll receive clean, structured, ready-to-use job posting data, including job titles, company names, seniority levels, industries, locations, salaries, and employment types.

    Choose your preferred dataset delivery options for convenience:

    Receive datasets in various formats, including CSV, JSON, and more. Opt for storage solutions such as AWS S3, Google Cloud Storage, and more. Customize data delivery frequencies, whether one-time or per your agreed schedule.

    Why Choose Oxylabs Job Posting Datasets:

    1. Fresh and accurate data: Access clean and structured job posting datasets collected by our seasoned web scraping professionals, enabling you to dive into analysis.

    2. Time and resource savings: Focus on data analysis and your core business objectives while we efficiently handle the data extraction process cost-effectively.

    3. Customized solutions: Tailor our approach to your business needs, ensuring your goals are met.

    4. Legal compliance: Partner with a trusted leader in ethical data collection. Oxylabs is a founding member of the Ethical Web Data Collection Initiative, aligning with GDPR and CCPA best practices.

    Pricing Options:

    Standard Datasets: choose from various ready-to-use datasets with standardized data schemas, priced from $1,000/month.

    Custom Datasets: Tailor datasets from any public web domain to your unique business needs. Contact our sales team for custom pricing.

    Experience a seamless journey with Oxylabs:

    • Understanding your data needs: We work closely to understand your business nature and daily operations, defining your unique data requirements.
    • Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
    • Delivering data sample: We provide a sample for your feedback on data quality and the entire delivery process.
    • Continuous data delivery: We continuously collect public data and deliver custom datasets per the agreed frequency.

    Effortlessly access fresh job posting data with Oxylabs Job Posting Datasets.

  14. s

    Data from: Employment by occupation

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Jul 27, 2022
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    Race Disparity Unit (2022). Employment by occupation [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/work-pay-and-benefits/employment/employment-by-occupation/latest
    Explore at:
    csv(309 KB)Available download formats
    Dataset updated
    Jul 27, 2022
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

  15. EARN06: Gross weekly earnings by occupation

    • ons.gov.uk
    • cy.ons.gov.uk
    xls
    Updated May 13, 2025
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    Office for National Statistics (2025). EARN06: Gross weekly earnings by occupation [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/grossweeklyearningsbyoccupationearn06
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Gross weekly and hourly earnings by level of occupation, UK, quarterly, not seasonally adjusted. Labour Force Survey. These are official statistics in development.

  16. A

    Employee Earnings Report

    • data.boston.gov
    csv
    Updated Feb 28, 2025
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    Office of Human Resources (2025). Employee Earnings Report [Dataset]. https://data.boston.gov/dataset/employee-earnings-report
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    csv(1967674), csv(2780939), csv, csv(2535798), csv(3372412), csv(2597411), csv(2407767), csv(2519912), csv(13225)Available download formats
    Dataset updated
    Feb 28, 2025
    Dataset authored and provided by
    Office of Human Resources
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    Each year, the City of Boston publishes payroll data for employees. This dataset contains employee names, job details, and earnings information including base salary, overtime, and total compensation for employees of the City.

    See the "Payroll Categories" document below for an explanation of what types of earnings are included in each category.

  17. Average early career salary of Ivy League attendees 2024

    • statista.com
    Updated Dec 9, 2024
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    Statista (2024). Average early career salary of Ivy League attendees 2024 [Dataset]. https://www.statista.com/statistics/937905/ivy-league-average-early-career-salary/
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    Dataset updated
    Dec 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    In 2024, graduates of Princeton University and Harvard University had an average early career salary of 95,600 U.S. dollars, which was the highest early career salary of any Ivy League university. In comparison, graduates of Brown University had an average early career salary of 88,000 U.S. dollars.

  18. Leading U.S. colleges 2023/24, by starting and mid-career pay of graduates

    • ai-chatbox.pro
    • statista.com
    Updated May 31, 2025
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    Abigail Tierney (2025). Leading U.S. colleges 2023/24, by starting and mid-career pay of graduates [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstudy%2F11647%2Fwage-inequality-in-the-us-statista-dossier%2F%23XgboD02vawLKoDs%2BT%2BQLIV8B6B4Q9itA
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    Dataset updated
    May 31, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Abigail Tierney
    Description

    As of the 2023/24 academic year, graduates from the Massachusetts Institute of Technology (MIT) had a starting salary of 110,200 U.S. dollars, and a mid-career salary of 196,900 U.S. dollars. Top universities in the United States One of the top universities in the United States, Harvey Mudd College, is located in Claremont, California. Not only do graduates earn a high salaries after graduation, they also pay the most. In the academic year of 2020-2021, Harvey Mudd College was one of the most expensive school by total annual cost. The best university in the United States in 2021 belonged to the University of California, Berkeley. The Ivy League The Ivy League is a group of eight private universities in the Northeastern United States. It is not only a collegiate athletic conference, but also a group of highly respected academic institutions. They are usually regarded as the best eight universities in the United States and the world. They are extremely selective with their admissions process. However, these universities are extremely expensive to attend. Despite the high price tag, students who graduate from Princeton University have the highest early career salary out of all Ivy League attendees in 2021. This is compared to the overall expected starting salaries of recent college graduates across the United States, which was less than 35,000 U.S. dollars.

  19. C

    Employee Compensation

    • phoenixopendata.com
    csv
    Updated Feb 4, 2025
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    Finance (2025). Employee Compensation [Dataset]. https://www.phoenixopendata.com/dataset/employee-compensation
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    csv(1157062), csv(1227063), csv(1155675), csv(1200003), csv(1180681), csv(1222639), csv(1170123), csv(1210716), csv(1212523)Available download formats
    Dataset updated
    Feb 4, 2025
    Dataset authored and provided by
    Finance
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This data is subject to change at any time due to personnel actions that are consistent with the City's approved Pay Plan. Employee compensation is limited to the following pay: regular wages, over time, productivity enhancement, shift differential, standby, incentive pay, allowances, and leave payouts. The data is a snapshot as of December 31st of the reported year.

    Job descriptions, pay ranges, and benefits information is available at: https://www.phoenix.gov/hr/job-descriptions

    Total compensation information is available at: https://www.phoenix.gov/hr/current-jobs/total-compensation-information

    Employee terms by unit is available at: https://www.phoenix.gov/hr/employee-terms-by-unit

  20. d

    Global Web Data | Web Scraping Data | Job Postings Data | Source: Company...

    • datarade.ai
    .json
    + more versions
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    PredictLeads, Global Web Data | Web Scraping Data | Job Postings Data | Source: Company Website | 214M+ Records [Dataset]. https://datarade.ai/data-products/predictleads-web-data-web-scraping-data-job-postings-dat-predictleads
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    .jsonAvailable download formats
    Dataset authored and provided by
    PredictLeads
    Area covered
    Kuwait, Bosnia and Herzegovina, Virgin Islands (British), Northern Mariana Islands, Comoros, El Salvador, Kosovo, Bonaire, Guadeloupe, French Guiana
    Description

    PredictLeads Job Openings Data provides high-quality hiring insights sourced directly from company websites - not job boards. Using advanced web scraping technology, our dataset offers real-time access to job trends, salaries, and skills demand, making it a valuable resource for B2B sales, recruiting, investment analysis, and competitive intelligence.

    Key Features:

    ✅214M+ Job Postings Tracked – Data sourced from 92 Million company websites worldwide. ✅7,1M+ Active Job Openings – Updated in real-time to reflect hiring demand. ✅Salary & Compensation Insights – Extract salary ranges, contract types, and job seniority levels. ✅Technology & Skill Tracking – Identify emerging tech trends and industry demands. ✅Company Data Enrichment – Link job postings to employer domains, firmographics, and growth signals. ✅Web Scraping Precision – Directly sourced from employer websites for unmatched accuracy.

    Primary Attributes:

    • id (string, UUID) – Unique identifier for the job posting.
    • type (string, constant: "job_opening") – Object type.
    • title (string) – Job title.
    • description (string) – Full job description, extracted from the job listing.
    • url (string, URL) – Direct link to the job posting.
    • first_seen_at – Timestamp when the job was first detected.
    • last_seen_at – Timestamp when the job was last detected.
    • last_processed_at – Timestamp when the job data was last processed.

    Job Metadata:

    • contract_types (array of strings) – Type of employment (e.g., "full time", "part time", "contract").
    • categories (array of strings) – Job categories (e.g., "engineering", "marketing").
    • seniority (string) – Seniority level of the job (e.g., "manager", "non_manager").
    • status (string) – Job status (e.g., "open", "closed").
    • language (string) – Language of the job posting.
    • location (string) – Full location details as listed in the job description.
    • Location Data (location_data) (array of objects)
    • city (string, nullable) – City where the job is located.
    • state (string, nullable) – State or region of the job location.
    • zip_code (string, nullable) – Postal/ZIP code.
    • country (string, nullable) – Country where the job is located.
    • region (string, nullable) – Broader geographical region.
    • continent (string, nullable) – Continent name.
    • fuzzy_match (boolean) – Indicates whether the location was inferred.

    Salary Data (salary_data)

    • salary (string) – Salary range extracted from the job listing.
    • salary_low (float, nullable) – Minimum salary in original currency.
    • salary_high (float, nullable) – Maximum salary in original currency.
    • salary_currency (string, nullable) – Currency of the salary (e.g., "USD", "EUR").
    • salary_low_usd (float, nullable) – Converted minimum salary in USD.
    • salary_high_usd (float, nullable) – Converted maximum salary in USD.
    • salary_time_unit (string, nullable) – Time unit for the salary (e.g., "year", "month", "hour").

    Occupational Data (onet_data) (object, nullable)

    • code (string, nullable) – ONET occupation code.
    • family (string, nullable) – Broad occupational family (e.g., "Computer and Mathematical").
    • occupation_name (string, nullable) – Official ONET occupation title.

    Additional Attributes:

    • tags (array of strings, nullable) – Extracted skills and keywords (e.g., "Python", "JavaScript").

    📌 Trusted by enterprises, recruiters, and investors for high-precision job market insights.

    PredictLeads Dataset: https://docs.predictleads.com/v3/guide/job_openings_dataset

Share
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Click to copy link
Link copied
Close
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Statista (2024). Highest paying bachelor's degrees in the U.S. 2021/22, by mid-career pay [Dataset]. https://www.statista.com/statistics/633793/highest-paying-bachelor-degrees-in-the-us/
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Highest paying bachelor's degrees in the U.S. 2021/22, by mid-career pay

Explore at:
Dataset updated
Jul 5, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2021
Area covered
United States
Description

This statistic shows the leading bachelor's degrees with the highest mid-career salary in the U.S. in the academic year 2020/21. In 2020/21, petroleum engineering was ranked first with the mid-career salary of 182,000 U.S. dollars.

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