This transformed view of Employee Demographics - Public dataset counts the number of and percentage of city employees by race as self-reported by employee based on EEOC classification. This information is used by "City Employee vs. Community Demographics dataset" at https://citydata.mesaaz.gov/Economic-Development/Chart-Data-for-City-Employee-vs-Community-Demograp/bt2n-zimw

Explore demographic data on the Massachusetts executive branch workforce. Track our progress toward our goals to reflect the diversity of the people we serve, and to stand out as an employer of choice.

Filtered view of current employees as of dataset refresh date and includes employee job title, department name, EEO Category and Sworn status. This view redacts age group, race/ethnicity, gender and date of hire. For race/ethnicity and gender employee demographics see https://citydata.mesaaz.gov/Human-Resources/Employee-Demographics-Race-Ethnicity-Public/ty4p-25y2/about_data.

As of June 2022, 57.6 percent of employees in leadership roles at Meta were white, whilst 28.6 percent were Asian. Overall, 11.7 percent of employees in non-technical roles were Hispanic, and 11.2 percent were Black. Moreover, Asian employees accounted for the majority of employees in technical roles, making up 55.8 percent of employees in these positions.

Dataset provides the public with a snapshot of the County of Los Angeles workforce including the count of full-time permanent employees by department, employee demographics (i.e., ethnicity and gender) EEO Job Categories and, EEO Functions.

Employee demographic data analysis. Includes employee age group, union membership or employment group, length of service, home location, and employee type. This data is as of current year, not historical. Please Note : This data is scheduled to be refreshed at midnight Monday through Friday.

Employment data for Netflix revealed that roughly ** percent of Netflix's employees in the United States as of 2023 were Asian, and over ** percent were Hispanic. The majority of employees working for the streaming giant are white.

Comparing the percentage of city residents (community) ethnicity to the percentage of city employee ethnicity. Employee information comes from Employee Demographics: Ethnicity https://citydata.mesaaz.gov/Human-Resources/Employee-Demographics-Ethnicity/6kd3-uaks. Community information comes from Community Demographics: Ethnicity at https://citydata.mesaaz.gov/Census/Community-Demographics-Ethnicity/g34w-9rxw

As of January 2024, the majority of Google employees worldwide, almost 66 percent, were male. The distribution of male and female employees at Google hasn’t seen a big change over the recent years. In 2014 the share of female employees at Google was 30.6 percent. In 2021 this number has increased by only 3 percent. Considering that the total number of Google employees increased greatly between the years 2007 and 2020, the female quota among the employees had seen rather a small increase. Google as a company Google is a diverse internet company that provides a wide range of digital products and services. In 2022, the company’s global revenue was over 279 billion U.S. dollars. Most of its revenue, around 305 billion U.S. dollars, was from advertising. Among its services, the most popular ones are YouTube and Google Play. Male and female employees at tech companies Google is not the only tech company with a lower number of female employees. This pattern can be seen in other big tech companies too. In 2019, in a ranking of 20 leading tech companies worldwide, only 23andMe had more than a 50 percent share of female employees. The majority of tech companies in the ranking have far more male than female employees.

Employee demographics (Experiment 1).

This table contains demographics information for employees of the Chapel Hill Police Department. Current as of October 2016.

This data asset was created in response to House Report 117-401, which stated, "The Committee directs the USAID Administrator, in consultation with the Director of the Office of Personnel Management and the Director of the Office of Management and Budget, to submit a report to the appropriate congressional committees, not later than 180 days after enactment of this Act, on USAID's workforce data that includes disaggregated demographic data and other information regarding the diversity of the workforce of USAID. Such report shall include the following data to the maximum extent practicable and permissible by law: 1) demographic data of USAID workforce disaggregated by grade or grade-equivalent; 2) assessment of agency compliance with the Equal Employment Opportunity Commission Management Directive 715; and 3) data on the overall number of individuals who are part of the workforce, including all U.S. Direct Hires, personnel under personal services contracts, and Locally Employed staff at USAID. The report shall also be published on a publicly available website of USAID in a searchable database format." This data asset fulfills the final part of this requirement, to publish the data in a searchable database format. The data are compiled from USAID's 2021 MD-715 report, available at https://www.usaid.gov/reports/md-715. The original data source is the system National Finance Center Insight owned by the Treasury Department.

Introduction

Employee Recognition Statistics: Employee recognition means showing appreciation for an employee's hard Work and contributions to a company. It can be as simple as a thank-you note or a monthly bonus. The key is that recognition should feel personal, sincere, and meaningful for it to be effective. Getting employee recognition right is important because even small acts of appreciation can have a big impact on a company's success.

When employees are recognized, it can improve productivity, create a better work culture, and lower turnover rates. Properly recognizing employees leads to a more motivated and loyal workforce, which benefits the company overall. We shall shed more light on Employee Recognition Statistics through this article.

As of April 8, 45.9 percent of FBI employees were female, while 27.5 percent were part of a racial or ethnic minority in 2024. In comparison, only 4.7 percent of FBI employees in that year had a disability.

This is a synthetic dataset that contains information about 300 employees, each represented by three features: date_of_birth, date_of_joining, and gender. The date_of_birth and date_of_joining columns are provided in dd-mm-yyyy format, indicating the employee's age and tenure with the company respectively. The gender column includes values such as male, female, and other . The target variable, promoted, indicates whether an employee received a promotion (yes) or not (no). The dataset is logically structured such that employees who are older, have spent more time in the company, and identify as female have a higher likelihood of being promoted.

A comprehensive dataset featuring the latest employee motivation statistics, including factors influencing workplace motivation, engagement levels, productivity metrics, and psychological insights from various sources.

Data updated quarterly.Data Attributes and Definitions -- Department: The department the employee works in.- Department ID: The numeric identifier for the department (typically 4 digits).- Job: The name for the job assigned to the employee.- Category: Grouping of employees in similar jobs/leadership roles.- Sub Category: Secondary grouping of employees within a category.- Race/Ethnicity: The race/ethnicity category which the employee identifies with (self-identified).- Gender: Designates the employee's gender (self-identified).- Age: The chronological number (age) assigned to the employee based on date of birth.- Age Group: Grouping of employees having approximately the same age or age range.- Original Hire Date: Date upon which the employee was originally hired.- Last Hire Date: Date upon which an employee was hired; may be a rehire date.- Pay Class: Defines how the employee gets paid for hours worked based on defined rules (full-time, part-time, hourly, etc.)- Data As of: The date to which the given data applies to.

The county and region of the workers are determined by the office to which they are assigned. Adult Protective Services (APS): APS Investigations employees protect people age 65 and older and adults with disabilities from abuse, neglect, and financial exploitation by investigating and providing or arranging for services necessary to alleviate or prevent further maltreatment. Child Protective Investigations (CPI/CCI): Counts the number of active CPI and CPS staff on the last day of the fiscal year by staff type and demographics. Child Care Investigations (CCI), which is a part of CPI and include Day Care Investigations (DCI) and Residential Child Care Investigations (RCCI) are only available from 2018 onward. This is due to the split of those job functions from Child Care Licensing, which was a part of DFPS until 2017, when it was transferred to the Health and Human Services Commission (HHSC). Statewide Intake (SWI): Statewide Intake (SWI) serves as the “front door to the front line” for all DFPS programs. As the central point of contact for reports of abuse, neglect and exploitation of vulnerable Texans. SWI staff are available 24 hours a day, 7 days per week, 365 days per year. Prior to FY2018, all SWI staff were located in the Austin area. Visit dfps.texas.gov for information on all DFPS programs

As of June 2022, 37.1 percent of worldwide Meta employees were women, an increase of 0.5 percent in the previous year. Overall, almost 63 percent of the company were men. The company has reported diversity metrics since 2014, and whilst the share of women employed by the company has increased, men continue to account for the overall majority. Moreover, Meta have reported that women were more likely to accept remote job offers.

The Agency Report Table aggregates pay and employment characteristics in accordance with the requirements of Local Law 18 of 2019. The Table is a point-in-time snapshot of employees who were either active or on temporary leave (parental leave, military leave, illness, etc.) as of December 31st of each year the data is available (see Column "Data Year"). In addition, the Table contains snapshot data of active employees in seasonal titles as of June 30th. To protect the privacy of employees, the sign “<5” is used instead of the actual number for groups of less than five (5) employees, in accordance with the Citywide Privacy Protection Policies and Protocols. The Pay and Demographics Report, and the list of agencies included is available on the MODA Open Source Analytics Library: https://modaprojects.cityofnewyork.us/local-law-18/

Each row represents a group of employees with a common agency, EEO-4 Job Category, pay band, employee status and demographic attributes, which include race, ethnicity and gender.