100+ datasets found
  1. data-science-job-salaries

    • huggingface.co
    Updated Aug 15, 2022
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    fastai X Hugging Face Group 2022 (2022). data-science-job-salaries [Dataset]. https://huggingface.co/datasets/hugginglearners/data-science-job-salaries
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 15, 2022
    Dataset provided by
    Hugging Facehttps://huggingface.co/
    Authors
    fastai X Hugging Face Group 2022
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    Dataset Card for Data Science Job Salaries

      Dataset Summary
    
    
    
    
    
      Content
    

    Column Description

    work_year The year the salary was paid.

    experience_level The experience level in the job during the year with the following possible values: EN Entry-level / Junior MI Mid-level / Intermediate SE Senior-level / Expert EX Executive-level / Director

    employment_type The type of employement for the role: PT Part-time FT Full-time CT Contract FL Freelance

    job_title… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/data-science-job-salaries.

  2. F

    Employed full time: Wage and salary workers: Compensation, benefits, and job...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
    + more versions
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    (2025). Employed full time: Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over [Dataset]. https://fred.stlouisfed.org/series/LEU0257856200A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over (LEU0257856200A) from 2011 to 2024 about occupation, jobs, full-time, compensation, benefits, salaries, workers, 16 years +, wages, employment, and USA.

  3. A

    ‘Employee Salaries - 2020’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Feb 26, 2014
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2014). ‘Employee Salaries - 2020’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-employee-salaries-2020-1182/latest
    Explore at:
    Dataset updated
    Feb 26, 2014
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Employee Salaries - 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1fc1fc94-d685-4c4f-9525-6e6079165315 on 26 January 2022.

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

    Annual salary information including gross pay and overtime pay for all active, permanent employees of Montgomery County, MD paid in calendar year 2020. This information will be published annually each year.

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

  4. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Data%20Analyst%20Engineering
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Data Analyst Engineering from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Data Analyst Engineering relative to other fields. This data is essential for students assessing the return on investment of their education in Data Analyst Engineering, providing a clear picture of financial prospects post-graduation.

  5. 2025 Jobs and Salaries in Data Science

    • kaggle.com
    Updated Jan 29, 2025
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    Hina Ismail (2025). 2025 Jobs and Salaries in Data Science [Dataset]. https://www.kaggle.com/datasets/sonialikhan/2025-jobs-and-salaries-in-data-science/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 29, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Hina Ismail
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    🚀 Data Science Careers in 2025: Jobs and Salary Trends in Pakistan 🚀 Data Science is one of the fastest-growing fields, and by 2025, the demand for skilled professionals in Pakistan will only increase. If you’re considering a career in Data Science, here’s what you need to know about the top jobs and salary trends.

    🔍 Top Data Science Jobs in 2025 1) Data Scientist Avg Salary: PKR 1.2M - 2.5M/year (Entry-Level), PKR 3M - 6M/year (Experienced) Skills: Python, R, Machine Learning, Data Visualization

    2) Data Analyst Avg Salary: PKR 800K - 1.5M/year (Entry-Level), PKR 2M - 3.5M/year (Experienced) Skills: SQL, Excel, Tableau, Power BI

    3) Machine Learning Engineer Avg Salary: PKR 1.5M - 3M/year (Entry-Level), PKR 4M - 7M/year (Experienced) Skills: TensorFlow, PyTorch, Deep Learning, NLP

    4)Business Intelligence Analyst Avg Salary: PKR 1M - 2M/year (Entry-Level), PKR 2.5M - 4M/year (Experienced) Skills: Data Warehousing, ETL, Dashboarding

    5) AI Research Scientist Avg Salary: PKR 2M - 4M/year (Entry-Level), PKR 5M - 10M/year (Experienced) Skills: AI Algorithms, Research, Advanced Mathematic

    💡 Why Choose Data Science? High Demand: Every industry in Pakistan needs data professionals. Attractive Salaries: Competitive pay based on technical expertise. Growth Opportunities: Unlimited career growth in this field.

    📈 Salary Trends Entry-Level: PKR 800K - 1.5M/year Mid-Level: PKR 2M - 4M/year Senior-Level: PKR 5M+ (depending on expertise and industry)

    🛠️ How to Get Started? Learn Skills: Focus on Python, SQL, Machine Learning, and Data Visualization. Build Projects: Work on real-world datasets to create a strong portfolio. Network: Connect with industry professionals and join Data Science communities.

    work_year: The year in which the data was recorded. This field indicates the temporal context of the data, important for understanding salary trends over time.

    job_title: The specific title of the job role, like 'Data Scientist', 'Data Engineer', or 'Data Analyst'. This column is crucial for understanding the salary distribution across various specialized roles within the data field.

    job_category: A classification of the job role into broader categories for easier analysis. This might include areas like 'Data Analysis', 'Machine Learning', 'Data Engineering', etc.

    salary_currency: The currency in which the salary is paid, such as USD, EUR, etc. This is important for currency conversion and understanding the actual value of the salary in a global context.

    salary: The annual gross salary of the role in the local currency. This raw salary figure is key for direct regional salary comparisons.

    salary_in_usd: The annual gross salary converted to United States Dollars (USD). This uniform currency conversion aids in global salary comparisons and analyses.

    employee_residence: The country of residence of the employee. This data point can be used to explore geographical salary differences and cost-of-living variations.

    experience_level: Classifies the professional experience level of the employee. Common categories might include 'Entry-level', 'Mid-level', 'Senior', and 'Executive', providing insight into how experience influences salary in data-related roles.

    employment_type: Specifies the type of employment, such as 'Full-time', 'Part-time', 'Contract', etc. This helps in analyzing how different employment arrangements affect salary structures.

    work_setting: The work setting or environment, like 'Remote', 'In-person', or 'Hybrid'. This column reflects the impact of work settings on salary levels in the data industry.

    company_location: The country where the company is located. It helps in analyzing how the location of the company affects salary structures.

    company_size: The size of the employer company, often categorized into small (S), medium (M), and large (L) sizes. This allows for analysis of how company size influences salary.

  6. 2025 Green Card Report for Data Analyst

    • myvisajobs.com
    Updated Jan 16, 2025
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    MyVisaJobs (2025). 2025 Green Card Report for Data Analyst [Dataset]. https://www.myvisajobs.com/reports/green-card/job-title/data-analyst/
    Explore at:
    Dataset updated
    Jan 16, 2025
    Dataset provided by
    MyVisaJobs.com
    Authors
    MyVisaJobs
    License

    https://www.myvisajobs.com/terms-of-service/https://www.myvisajobs.com/terms-of-service/

    Variables measured
    Salary, Job Title, Petitions Filed
    Description

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

  7. A

    ‘Baltimore City Employee Salaries’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Oct 29, 2021
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2021). ‘Baltimore City Employee Salaries’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-baltimore-city-employee-salaries-ac87/latest
    Explore at:
    Dataset updated
    Oct 29, 2021
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Area covered
    Baltimore
    Description

    Analysis of ‘Baltimore City Employee Salaries’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/09dd5c6e-6cc5-4322-adf7-8c0a6616dbc7 on 12 February 2022.

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

    This dataset includes Baltimore City employee salaries and gross pay from fiscal year 2011 through last fiscal year and includes employees who were employed on June 30 of the last fiscal year. For fiscal years 2020 and prior, data are extracted from the ADP payroll system. For fiscal year 2021, the data are combined from the ADP system and the Workday enterprise resource planning system which now includes payroll.

    Change Log
    2021-10-29:
    - Added FY2021 data
    - Metadata added
    - Columns renamed to a standard format
    - Youth workers not employed by City removed
    - Agency names reformatted with Workday conventions

    Data Dictionary

    field_namedescriptiondata_typerange_of_possible_valuesexample_values
    firstNameThe first name of the employee.TextN/A
    middleInitialThe middle initial of the employee.TextN/A
    lastNameThe last name of the employee.TextN/A
    jobClassThe job classification of the employee. Job classifications are a standardized system of job responsibilities and pay and are frequently not the same as an employee's functional title. Participants in Youthworks who were not employed by the City are not included in this dataset.CategoryThere are 1,898 unique job classficiations in this dataset."911 OPERATOR" ; "LABORER" ; "CDL DRIVER I" ; "OPERATIONS MANAGER III"
    agencyIDA unique identifier for the agency or department the employee works for. There is a one-to-one relationship between the agencyID and agencyName fields.TextThere are 73 unique agencyID values corresponding to 73 unique agencyName values."A01" ; "A54"; "R01"
    agencyNameThe name of the agency or department the employee works for. There is a one-to-one relationship between the agencyID and agencyName fields. The agencyID is typically a letter followed by two numbers though there are a few exceptions.TextThere are 73 unique agencyID values corresponding to 73 unique agencyName values."Police Department" ; "Public Works - Solid Waste (weekly)" ; "Convention Center"
    hireDateThe date the employee was hired.Date6/23/1951 through 6/30/20214/3/1979
    annualSalaryThe employee's base annual salary for the fiscal year.Number0 through 276375
    grossPayThe total sum of compensation the employee received during the fiscal year. To be included in this dataset the employee must have earned more than $0.00 in the fiscal year.Number1.71 through 373111.20
    fiscalYearThe fiscal year during which the employee worked for the city. Fiscal years for the City begin July 1 and end June 30 each year. Employees must have earned more than $0.00 during the fiscal year to be included for that year.CategoryFY2011 through FY2021"FY2021"

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

  8. A

    ‘Employee Salaries - 2019’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 27, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Employee Salaries - 2019’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-employee-salaries-2019-9698/latest
    Explore at:
    Dataset updated
    Jan 27, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Employee Salaries - 2019’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/da04581d-180f-4008-bb0d-70d830f9e673 on 27 January 2022.

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

    Annual salary information including gross pay and overtime pay for all active, permanent employees of Montgomery County, MD paid in calendar year 2019. This information will be published annually each year.

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

  9. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Avionics%20Specialist
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Avionics Specialist from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Avionics Specialist relative to other fields. This data is essential for students assessing the return on investment of their education in Avionics Specialist, providing a clear picture of financial prospects post-graduation.

  10. w

    Public Affairs Specialist List by Salary

    • data.wu.ac.at
    csv, json, xml
    Updated Oct 13, 2015
    + more versions
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    (2015). Public Affairs Specialist List by Salary [Dataset]. https://data.wu.ac.at/schema/data_oregon_gov/eDJyaS1yNW1x
    Explore at:
    json, xml, csvAvailable download formats
    Dataset updated
    Oct 13, 2015
    Description

    Salaries of state work force sorted by agency.

  11. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
    + more versions
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Specialist%20In%20Marketing%20Management
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Specialist In Marketing Management from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Specialist In Marketing Management relative to other fields. This data is essential for students assessing the return on investment of their education in Specialist In Marketing Management, providing a clear picture of financial prospects post-graduation.

  12. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Facial%20Specialist
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Facial Specialist from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Facial Specialist relative to other fields. This data is essential for students assessing the return on investment of their education in Facial Specialist, providing a clear picture of financial prospects post-graduation.

  13. f

    Data from: Average salary

    • froghire.ai
    Updated Apr 3, 2025
    + more versions
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    FrogHire.ai (2025). Average salary [Dataset]. https://www.froghire.ai/major/Education%2C%20Instructional%20Specialist
    Explore at:
    Dataset updated
    Apr 3, 2025
    Dataset provided by
    FrogHire.ai
    Description

    Explore the progression of average salaries for graduates in Education, Instructional Specialist from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Education, Instructional Specialist relative to other fields. This data is essential for students assessing the return on investment of their education in Education, Instructional Specialist, providing a clear picture of financial prospects post-graduation.

  14. F

    Employed full time: Wage and salary workers: Air traffic controllers and...

    • fred.stlouisfed.org
    json
    Updated Jan 22, 2025
    + more versions
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    (2025). Employed full time: Wage and salary workers: Air traffic controllers and airfield operations specialists occupations: 16 years and over: Women [Dataset]. https://fred.stlouisfed.org/series/LEU0254735000A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Wage and salary workers: Air traffic controllers and airfield operations specialists occupations: 16 years and over: Women (LEU0254735000A) from 2000 to 2024 about operating, air travel, travel, occupation, females, full-time, salaries, workers, 16 years +, wages, employment, and USA.

  15. H

    Physician Salary Database 2025

    • salarydr.com
    json
    Updated Jan 27, 2025
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    SalaryDr (2025). Physician Salary Database 2025 [Dataset]. https://www.salarydr.com
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jan 27, 2025
    Dataset authored and provided by
    SalaryDr
    License

    https://www.salarydr.com/termshttps://www.salarydr.com/terms

    Time period covered
    2020 - 2025
    Description

    Comprehensive physician salary data covering 75+ medical specialties with 2,500+ verified submissions from practicing physicians, residents, and medical students.

  16. 2025 Green Card Report for Senior Data Analyst

    • myvisajobs.com
    Updated Jan 16, 2025
    + more versions
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    MyVisaJobs (2025). 2025 Green Card Report for Senior Data Analyst [Dataset]. https://www.myvisajobs.com/reports/green-card/job-title/senior-data-analyst/
    Explore at:
    Dataset updated
    Jan 16, 2025
    Dataset provided by
    MyVisaJobs.com
    Authors
    MyVisaJobs
    License

    https://www.myvisajobs.com/terms-of-service/https://www.myvisajobs.com/terms-of-service/

    Variables measured
    Salary, Job Title, Petitions Filed
    Description

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

  17. Average Salary by Job Classification

    • kaggle.com
    Updated Mar 31, 2025
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    Sonawane Lalit (2025). Average Salary by Job Classification [Dataset]. https://www.kaggle.com/datasets/sonawanelalitsunil/average-salary-by-job-classification
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    Kaggle
    Authors
    Sonawane Lalit
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    Overview This dataset provides insights into salary distributions across various job classifications, enabling a deeper understanding of compensation trends across industries, experience levels, and geographical locations. It serves as a valuable resource for HR professionals, job seekers, researchers, and policymakers aiming to analyze pay scales, wage gaps, and salary progression trends.

    Data Sources The data is aggregated from multiple employment and compensation reports, salary surveys, and publicly available job postings. It has been cleaned, standardized, and structured to ensure consistency and usability for analytical purposes.

    Features Job Title: Specific title of the job (e.g., Data Analyst, Software Engineer, Marketing Manager).

    Job Classification: Broad category of jobs (e.g., IT, Finance, Healthcare, Education).

    Industry: The sector in which the job belongs (e.g., Technology, Banking, Retail).

    Experience Level: Categorized as Entry-level, Mid-level, or Senior-level.

    Education Requirement: Minimum qualification required for the job role.

    Average Salary (INR/USD/Other Currency): The median or mean salary for a particular job classification.

    Salary Range: The minimum and maximum salary offered for a role.

    Location: Country or region where the job is based.

    Employment Type: Full-time, Part-time, Contract, or Remote.

    Company Size: Small, Medium, or Large enterprises.

    Potential Use Cases Salary Benchmarking: Compare salary expectations across industries and job roles.

    Career Planning: Identify lucrative career paths based on salary trends.

    Wage Gap Analysis: Examine salary disparities by gender, location, or experience level.

    Cost of Living Adjustments: Assess salaries relative to regional economic conditions.

    HR and Recruitment Strategies: Optimize compensation packages to attract top talent.

    Acknowledgments The dataset is compiled from various salary reports and job market research sources. Special thanks to contributors and organizations providing employment data for analysis.

    License This dataset is shared for educational, research, and analytical purposes. Please ensure compliance with relevant data usage policies before any commercial applications.

    Get Started The dataset can be explored using Python (Pandas), R, SQL, or visualization tools like Tableau and Power BI. Sample notebooks and analyses are available in the Kaggle notebook section.

  18. T

    United States - Employed full time: Wage and salary workers: Compensation,...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Aug 26, 2020
    + more versions
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    TRADING ECONOMICS (2020). United States - Employed full time: Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over: Women [Dataset]. https://tradingeconomics.com/united-states/employed-full-time-wage-and-salary-workers-compensation-benefits-and-job-analysis-specialists-occupations-16-years-and-over-women-fed-data.html
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Aug 26, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Employed full time: Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over: Women was 39.00000 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, United States - Employed full time: Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over: Women reached a record high of 59.00000 in January of 2012 and a record low of 31.00000 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Employed full time: Wage and salary workers: Compensation, benefits, and job analysis specialists occupations: 16 years and over: Women - last updated from the United States Federal Reserve on June of 2025.

  19. Data Analyst: 2025 H-1B Report by Job Title

    • myvisajobs.com
    Updated Jan 16, 2025
    + more versions
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    MyVisaJobs (2025). Data Analyst: 2025 H-1B Report by Job Title [Dataset]. https://www.myvisajobs.com/reports/h1b/job-title/data-analyst/
    Explore at:
    Dataset updated
    Jan 16, 2025
    Dataset provided by
    MyVisaJobs.com
    Authors
    MyVisaJobs
    License

    https://www.myvisajobs.com/terms-of-service/https://www.myvisajobs.com/terms-of-service/

    Variables measured
    Number of LCA, Average Salary, H1B Visa Sponsor
    Description

    H-1B visa sponsorship trends for Data Analyst, covering top employers, salary insights, approval rates, and geographic distribution. Explore how job title impacts the U.S. job market under the H-1B program.

  20. H

    Healthcare Professional Salary Data

    • healthsalaries.com
    json
    Updated May 20, 2025
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    Healthcare Salary Transparency Platform (2025). Healthcare Professional Salary Data [Dataset]. https://healthsalaries.com/browse-salaries
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 20, 2025
    Dataset authored and provided by
    Healthcare Salary Transparency Platform
    Description

    Comprehensive database of verified healthcare professional salaries across different specialties and locations

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fastai X Hugging Face Group 2022 (2022). data-science-job-salaries [Dataset]. https://huggingface.co/datasets/hugginglearners/data-science-job-salaries
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data-science-job-salaries

hugginglearners/data-science-job-salaries

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CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Aug 15, 2022
Dataset provided by
Hugging Facehttps://huggingface.co/
Authors
fastai X Hugging Face Group 2022
License

https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

Description

Dataset Card for Data Science Job Salaries

  Dataset Summary





  Content

Column Description

work_year The year the salary was paid.

experience_level The experience level in the job during the year with the following possible values: EN Entry-level / Junior MI Mid-level / Intermediate SE Senior-level / Expert EX Executive-level / Director

employment_type The type of employement for the role: PT Part-time FT Full-time CT Contract FL Freelance

job_title… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/data-science-job-salaries.

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