Master's (MS) in Human Capital Analytics and Technology (STEM)

Simply put, human capital analytics and technology is the use of talent data, tools, techniques and new technologies to improve talent and business outcomes. It helps organizations optimize the employee experience, improve productivity and develop actionable talent acquisition and retention strategies.

The number of occupations that require a combination of critical thinking, technical competence and digital skills continue to grow. The U.S. Department of Labor projects that STEM occupations will grow by almost 11% through 2031, more than twice as fast as the growth for other occupations. The NYU SPS MS in Human Capital Analytics and Technology degree has been designated by the U.S. Department of Homeland Security as a STEM program. This is particularly important for international students with an F-1 visa who are interested in gaining work experience in the U.S. after their degree completion. Earning a degree from a STEM designated program allows international students to extend their Optional Practical Training (OPT) for an additional year (up to two years total).

Human capital analytics and technology professionals are critical to helping organizations use the increasing amounts of data available to make data-informed talent and business decisions. The U.S. Bureau of Labor Statistics projects a faster-than-average growth rate of 8% through 2031 for HR specialist occupations such as human capital analytics.

The curriculum for the Master’s in Human Capital Analytics and Technology includes 7 core requirements and 6 elective courses. The People and Organization Management course is an immersion experience that includes a 5-day intensive that allows students to quickly coalesce as a cohort group and get exposure to concepts, cutting-edge approaches, and technologies that help them understand how analytics are used. In addition to the core requirements and elective courses, students must complete the Human Capital Analytics and Technology capstone project at the end of their study, which provides them with the experience of working in teams on a real business problem with a partnering organization.

NYU SPS graduates of the Master's in Human Capital Analytics and Technology program go on to a variety of roles within corporations, consulting firms, educational institutions and nonprofits. Many graduates take on roles within human capital analytics teams while others have roles in talent management, compensation and benefits, HR operations, talent development, talent acquisition, workforce planning and as HR business partners. In short, having a Master of Science in Human Capital Analytics and Technology allows our graduates to use their analytics skills across all areas of HR.

Professionals in the human capital analytics and technology field help organizations with day-to-day operations as well as long-term strategic planning. If you enjoy solving problems and answering questions using data and have a passion for improving organizational performance and the lives of people at work, you will find a career in human capital analytics and technology to be rewarding.

Human resource analytics is used to understand, manage, and optimize various aspects of an organization's human capital. It leverages data on employees, their skills, performance, and other relevant factors to make informed decisions about workforce management.

Becoming a human capital analyst typically requires a combination of education, analytics skills development, and practical experience. People interested in this career path can obtain a relevant undergraduate degree or fast-track their career with a Master of Science in Human Capital Analytics and Technology.

The three levels of human capital analytics are descriptive analytics, diagnostic analytics and predictive analytics. Descriptive analytics focuses on summarizing historical data to help businesses identify trends and patterns. Diagnostic Analytics goes a step further by exploring the reasons behind these trends, and predictive analytics aims to predict and prevent unwanted outcomes.

The four types of human resource analytics are descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. The first three levels are outlined above. The 4th level, prescriptive analytics, goes beyond predicting future outcomes to provide recommendations for action.

Yes, the average growth rate for all careers from 2022 to 2023 was 3% according to the Bureau of Labor Statistics. The BLS reported that careers in HR analysis were projected to grow above average from 2022 to 2023 at 7%. Human resource analytics is in demand and has been gaining increasing importance in the business world. Organizations are recognizing the value of leveraging data to make informed decisions about their workforce.

A degree in human resource analytics or a closely related field can provide a solid foundation for a career in human resource analytics. However, the specific degree requirements can vary depending on the employer and the nature of the job.

The terms "people analytics" and "human resources analytics" are often used interchangeably, and both refer to the application of data analysis and statistical methods to report findings, interpret trends and improve various aspects of the workforce. In general, people analytics is the broad term to encompass the entire workforce, while human resource analytics is specific to the strategic management of talent within an organization.

The terms "people analytics" and "talent analytics" are closely related and are often used interchangeably, but people analytics is the broader term to encompass the entire workforce. Talent analytics, on the other hand, focuses on the strategic management of talent within the organization.