This dataset has been published by the Human Resources Department of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.Distributed bydata.virginiabeach.gov2405 Courthouse Dr.Virginia Beach, VA 23456EntityEmployee SalariesPoint of ContactHuman ResourcesSherri Arnold, Human Resources Business Partner IIIsharnold@vbgov.com757-385-8804Elda Soriano, HRIS Analystesoriano@vbgov.com757-385-8597AttributesColumn: DepartmentDescription: 3-letter department codeColumn: Department DivisionDescription: This is the City Division that the position is assigned to.Column: PCNDescription: Tracking number used to reference each unique position within the City.Column: Position TitleDescription: This is the title of the position (per the City’s pay plan).Column: FLSA Status Description: Represents the position’s status with regards to the Fair Labor Standards Act (FLSA) “Exempt” - These positions do not qualify for overtime compensation – Generally, a position is classified as FLSA exempt if all three of the following criteria are met: 1) Paid at least $47,476 per year ($913 per week); 2) Paid on a salary basis - generally, salary basis is defined as having a guaranteed minimum amount of pay for any work week in which the employee performs any work; 3) Perform exempt job duties - Job duties are split between three classifications: executive, professional, and administrative. All three have specific job functions which, if present in the employee’s regular work, would exempt the individual from FLSA. Employees may also be exempt from overtime compensation if they are a “highly compensated employee” as defined by the FLSA or the position meets the criteria for other enumerated exemptions in the FLSA.“Non-exempt” – These positions are eligible for overtime compensation - positions classified as FLSA non-exempt if they fail to meet any of exempt categories specified in the FLSA. Column: Initial Hire DateDescription: This is the date that the full-time employee first began employment with the City.Column: Date in TitleDescription: This is the date that the full-time employee first began employment in their current position.Column: SalaryDescription: This is the annual salary of the full-time employee or the hourly rate of the part-time employee.Frequency of dataset updateMonthly
About this itemBack in 2017, I made a Cascade story map to compile GIS career resources for my current and future interns. Fast forward seven years, and I finally rebuilt it as an ArcGIS StoryMap. From job title descriptions to certifications and to salaries, it covers the main areas I find emerging professionals asking about when they're looking at a career in GIS. There are multiple shout outs to the Consortium in it too, of course.😎Author/ContributorJohn NergeOrganizationPersonal workOrg Websitehttps://bit.ly/JohnNerge
Explore the progression of average salaries for graduates in Gis 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 Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Gis, providing a clear picture of financial prospects post-graduation.
Classification establishes and maintains the County's job classifications and compensation systems and practices, with equity, consistency, and due regard for pay competitiveness. Positions are analyzed and assigned to appropriate job classificationsJob Descriptions -- Frequently Asked Questions -- Classification and Compensation Documents
Explore the progression of average salaries for graduates in Transportation And Gis 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 Transportation And Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Transportation And Gis, providing a clear picture of financial prospects post-graduation.
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The County of Suffolk Annual Salaries File for the Year 2020 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.
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The County of Suffolk Annual Salaries File for the Year 2024 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.
Explore the progression of average salaries for graduates in Geography (Gis Specialty) 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 Geography (Gis Specialty) relative to other fields. This data is essential for students assessing the return on investment of their education in Geography (Gis Specialty), providing a clear picture of financial prospects post-graduation.
Tempe is among Arizona's most educated cities, lending to a creative, smart atmosphere. With more than a dozen colleges, trade schools and universities, about 40 percent of our residents over the age of 25 have Bachelor's degrees or higher. Having such an educated and accessible workforce is a driving factor in attracting and growing jobs for residents in the region.The City of Tempe is a member of the Greater Phoenix Economic Council (GPEC) and with the membership staff tracks collaborative efforts to recruit business prospects and locates. The Greater Phoenix Economic Council (GPEC) is a performance-driven, public-private partnership. GPEC partners with the City of Tempe, Maricopa County, 22 other communities and more than 170 private-sector investors to promote the region’s competitive position and attract quality jobs that enable strategic economic growth and provide increased tax revenue for Tempe.This dataset provides the target and actual job creation numbers for the City of Tempe and Greater Phoenix Economic Council (GPEC). The job creation target for Tempe is calculated by multiplying GPEC's target by twice Tempe's proportion of the population.This page provides data for the New Jobs Created performance measure.The performance measure dashboard is available at 5.02 New Jobs Created.Additional InformationSource:Contact: Madalaine McConvilleContact Phone: 480-350-2927Data Source Type: Excel filesPreparation Method: Extracted from GPEC monthly and annual reports and proprietary excel filesPublish Frequency: AnnuallyPublish Method: ManualData Dictionary
https://www.myvisajobs.com/terms-of-service/https://www.myvisajobs.com/terms-of-service/
A dataset that explores Green Card sponsorship trends, salary data, and employer insights for gis in the U.S.
Explore the progression of average salaries for graduates in Remote Sensing/Gis 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 Remote Sensing/Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Remote Sensing/Gis, providing a clear picture of financial prospects post-graduation.
Explore the progression of average salaries for graduates in Cartology And Gis 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 Cartology And Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Cartology And Gis, providing a clear picture of financial prospects post-graduation.
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View the diversity of challenges and opportunities across America's counties within different types of rural regions and communities. Get statistics on people, jobs, and agriculture.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Data file GIS API Services Interactive map Zip of CSV files For complete information, please visit https://data.gov.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for geographic information science (gis) in the U.S.
description: Dataset featuring the full-time, part-time and seasonal jobs, as well as internships posted on the City's job portal @ https://www.raleighnc.gov/jobs This dataset is updated weekdays by 9am and does not contain past (non-active) postings.; abstract: Dataset featuring the full-time, part-time and seasonal jobs, as well as internships posted on the City's job portal @ https://www.raleighnc.gov/jobs This dataset is updated weekdays by 9am and does not contain past (non-active) postings.
JOBS PROXIMITY INDEXSummaryThe jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. E represents the number of jobs in block-group j, and L is the number of workers in block-group j. The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts. InterpretationValues are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood. Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2017. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 8. To learn more about the Jobs Proximity Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020
Explore the progression of average salaries for graduates in Geographic Information Systems Gis 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 Geographic Information Systems Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Geographic Information Systems Gis, providing a clear picture of financial prospects post-graduation.
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The County of Suffolk Annual Salaries File for the Year 2016 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.
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A dataset that explores Green Card sponsorship trends, salary data, and employer insights for forest engineering (gis) in the U.S.
Explore the progression of average salaries for graduates in Geographical Information Systems Gis 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 Geographical Information Systems Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Geographical Information Systems Gis, providing a clear picture of financial prospects post-graduation.
This dataset has been published by the Human Resources Department of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.Distributed bydata.virginiabeach.gov2405 Courthouse Dr.Virginia Beach, VA 23456EntityEmployee SalariesPoint of ContactHuman ResourcesSherri Arnold, Human Resources Business Partner IIIsharnold@vbgov.com757-385-8804Elda Soriano, HRIS Analystesoriano@vbgov.com757-385-8597AttributesColumn: DepartmentDescription: 3-letter department codeColumn: Department DivisionDescription: This is the City Division that the position is assigned to.Column: PCNDescription: Tracking number used to reference each unique position within the City.Column: Position TitleDescription: This is the title of the position (per the City’s pay plan).Column: FLSA Status Description: Represents the position’s status with regards to the Fair Labor Standards Act (FLSA) “Exempt” - These positions do not qualify for overtime compensation – Generally, a position is classified as FLSA exempt if all three of the following criteria are met: 1) Paid at least $47,476 per year ($913 per week); 2) Paid on a salary basis - generally, salary basis is defined as having a guaranteed minimum amount of pay for any work week in which the employee performs any work; 3) Perform exempt job duties - Job duties are split between three classifications: executive, professional, and administrative. All three have specific job functions which, if present in the employee’s regular work, would exempt the individual from FLSA. Employees may also be exempt from overtime compensation if they are a “highly compensated employee” as defined by the FLSA or the position meets the criteria for other enumerated exemptions in the FLSA.“Non-exempt” – These positions are eligible for overtime compensation - positions classified as FLSA non-exempt if they fail to meet any of exempt categories specified in the FLSA. Column: Initial Hire DateDescription: This is the date that the full-time employee first began employment with the City.Column: Date in TitleDescription: This is the date that the full-time employee first began employment in their current position.Column: SalaryDescription: This is the annual salary of the full-time employee or the hourly rate of the part-time employee.Frequency of dataset updateMonthly