Meta Platforms had ****** full-time employees as of December 2024, down from ****** people in 2023. As of December 2023, more than ******* employees at tech companies worldwide were laid off throughout the year across more than 1,000 companies. Facebook: how it all beganIn 2003, a sophomore at named Mark Zuckerberg hacked into protected areas of the university's computer network in order to find photos of other students. He then would pair two of them next to each other on a program called “Facemash” and ask users to choose the more attractive person. At the beginning of 2004, Zuckerberg launched “The Facebook,” a social network dedicated to Harvard students, which later grew to encompass Columbia, Yale and Stanford. The popularity of this new service sky-rocketed and in mid-2004, Zuckerberg interrupted his studies and moved his operation to Palo Alto, California, in the heart of Silicon Valley. By 2006, Facebook was open to the general public. In 2020, the company reported almost ** billion U.S. dollars in revenue and a net income of ***** billion US dollars. It is also the most popular social network in the world, with *** billion monthly active users as of December 2020. Facebook employee diversity criticismLike many other tech companies, Facebook has been criticized for having a diversity problem. As of June 2020, tech positions, as well as management roles in U.S. offices were overwhelmingly occupied by men. Furthermore, almost ** percent of Facebook employees in the U.S. are White and only *** percent are African-American, which has sparked concern regarding representation and equal opportunities. Around **** percent of senior level positions are occupied by White employees and only *** percent by Hispanic-Americans.

Meta reported 67.32K in Employees for its fiscal year ending in December of 2023. Data for Meta | FB - Employees Total Number including historical, tables and charts were last updated by Trading Economics this last July in 2025.

In fiscal year 2024, the total number of employees at Meta Platforms was 74,067. The employee count increasedby 6,750 from 67,317 (in 2023) to 74,067 (in 2024). It represents a 10.03% year-over-year growth in employee count.

In 2022, 6.5 percent of Meta employees in the United States identified as Hispanic and 4.9 percent identified as Black. Asian employees accounted for over 46.5 percent of the overall workforce, whilst white employees made up 37.6 percent of Meta's workforce.

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.

Meta Materials number of employees from 2011 to 2024. Number of employees can be defined as a measure of financial performance calculated as operating cash flow minus capital expenditures, expressed on a per share basis

This dataset is about companies. It has 17 rows and is filtered where the company is Meta. It features 5 columns: employees, CEO, CEO gender, and CEO approval.

In 2023, Amazon.com was the top-ranked internet company based on number of employees. The e-commerce giant reported a workforce of more than **** million employees. Amazon has consistently topped the ranking as the online company with the biggest workforce, but the global COVID-19 pandemic has widened the gap as e-commerce has boomed since. During the same period, Meta (formerly Facebook Inc.) had a total of ****** full-time employees. Additionally, Google's parent company Alphabet had ******* full-time workers in 2024.

As of June 2022, only 37.1 percent of all global Meta Platforms employees were women. The majority of employees were male. Overall, women made up 25.8 percent of tech roles and 60.5 percent of non-tech roles.

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.

This is dataset includes a list of meta-organizations, selected from the book Tietje, C., & Brouder, A. (Eds.). (2009). Handbook of Transnational Economic Governance Regimes. Martinus Nijhoff Publishers. It includes the name, the website, the chapter reference, and an analysis of both the case description in the book and the website of the meta-organization to understand the type workforce (member employees, meta-organization employees, rotation, and the mix thereof), as well as whether the workforce is hosted or hosting other meta-organizational workforces. The dataset has been utilized in a chapter on workforces in meta-organizations in a book edited by Berkowitz, Bor and Brunsson.

List of employees and associated meta data that will be used to generate agency, department, office, and section directories.

Facebook probably needs no introduction; nonetheless, here is a quick history of the company. The world’s biggest and most-famous social network was launched by Mark Zuckerberg while he was a...

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Meta. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Meta, the median income for all workers aged 15 years and older, regardless of work hours, was $40,000 for males and $25,893 for females.

These income figures highlight a substantial gender-based income gap in Meta. Women, regardless of work hours, earn 65 cents for each dollar earned by men. This significant gender pay gap, approximately 35%, underscores concerning gender-based income inequality in the city of Meta.

Surprisingly, within the subset of full-time workers, women earn a higher income than men, earning 1.08 dollars for every dollar earned by men. This suggests that within full-time roles, womens median incomes significantly surpass mens, contrary to broader workforce trends.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Meta median household income by race. You can refer the same here

List of employees and associated meta data that will be used to generate agency, department, office, and section directories.

The tech industry had a rough start to 2024. Technology companies worldwide saw a significant reduction in their workforce in the first quarter of 2024, with over 57 thousand employees being laid off. By the second quarter, layoffs impacted more than 43 thousand tech employees. In the final quarter of the year around 12 thousand employees were laid off. Layoffs impacting all global tech giants Layoffs in the global market escalated dramatically in the first quarter of 2023, when the sector saw a staggering record high of 167.6 thousand employees losing their jobs. Major tech giants such as Google, Microsoft, Meta, and IBM all contributed to this figure during this quarter. Amazon, in particular, conducted the most rounds of layoffs with the highest number of employees laid off among global tech giants. Industries most affected include the consumer, hardware, food, and healthcare sectors. Notable companies that have laid off a significant number of staff include Flink, Booking.com, Uber, PayPal, LinkedIn, and Peloton, among others. Overhiring led the trend, but will AI keep it going? Layoffs in the technology sector started following an overhiring spree during the COVID-19 pandemic. Initially, companies expanded their workforce to meet increased demand for digital services during lockdowns. However, as lockdowns ended, economic uncertainties persisted and companies reevaluated their strategies, layoffs became inevitable, resulting in a record number of 263 thousand laid off employees in the global tech sector by trhe end of 2022. Moreover, it is still unclear how advancements in artificial intelligence (AI) will impact layoff trends in the tech sector. AI-driven automation can replace manual tasks leading to workforce redundancies. Whether through chatbots handling customer inquiries or predictive algorithms optimizing supply chains, the pursuit of efficiency and cost savings may result in more tech industry layoffs in the future.

Introduction

Employee Layoff Statistics: Employee layoffs are a prevalent cost-cutting strategy employed by companies during economic downturns or organizational restructuring. In 2024, the technology sector alone witnessed over 136,000 job losses across 422 companies, with major firms like Intel, Cisco, and IBM implementing significant workforce reductions. Intel, for instance, announced plans to lay off 15,000 employees, constituting more than 15% of its workforce, as part of a USD 10 billion cost-reduction initiative.

The financial implications of layoffs extend beyond severance packages. For example, when Meta Platforms Inc. laid off 11,000 employees in November 2022, it incurred approximately USD 975 million in severance costs, averaging over USD 88,000 per employee. Additionally, companies often face indirect costs such as decreased productivity among remaining staff, increased turnover, and higher unemployment insurance taxes.

In India, the impact of layoffs has been significant as well. By August 2024, at least 8,000 individuals had been affected by job cuts, with companies like Paytm announcing reductions of up to 3,500 employees. Furthermore, Reliance Industries reportedly reduced its workforce by 11%, equating to approximately 42,000 jobs, to enhance cost efficiency.

These figures underscore the widespread and multifaceted impact of layoffs on both organizations and employees, highlighting the importance of strategic planning and support mechanisms during such transitions. This article includes recent trends and facts from insights gathered in 2024 and 2025. Let's delve into key statistics to get a clearer picture of the topic.

Scholars have conducted numerous studies on how distal antecedents influence motivational states, subsequently affecting employee proactive work behavior. However, there is still debate about the strength of the effects different motivational states have on employee proactive behavior. This paper employs meta-analysis to explore the motivational mechanism proposed in Parker's (2010) model of proactive work behavior. It analyzes the relative strength of the effects of three motivational states—"can do," "reason to," and "energized to"—on employee proactive work behavior. Through literature screening, this study conducted a meta-analysis of 94 Chinese and English studies (with a total sample size of 30,724) that adopted Parker's theoretical model. It compared the correlations between distal antecedents, different motivational perspectives, and proactive work behavior. The results show that all three motivational states positively influence proactive work behavior. "Reason to" has a stronger effect on proactive work behavior compared to the other motivational states, and "can do" is stronger than "energized to," highlighting the importance of "reason to" in promoting employee proactive work behavior. Further discussion on this topic is provided.

AI Agent Employee Agent Meta and Traffic Dataset in AI Agent Marketplace | AI Agent Directory | AI Agent Index from DeepNLP

This dataset is collected from AI Agent Marketplace Index and Directory at http://www.deepnlp.org, which contains AI Agents's meta information such as agent's name, website, description, as well as the monthly updated Web performance metrics, including Google,Bing average search ranking positions, Github Stars, Arxiv References, etc. The dataset is helpful for… See the full description on the dataset page: https://huggingface.co/datasets/DeepNLP/ai-agent-employee.

In 2024, Apple generated the highest revenue per employee amongst the leading tech companies (by market capitalization) with **** million U.S. dollars. Meta and NVIDIA were the only other companies with revenues per employee exceeding *** million U.S. dollars.