The jobs with a critical mass of young talent tend to require little to no education and not pay super well.
This isn’t a startling revelation—most young workers can’t be choosy when trying to gain real-world experience or pay for college—but this trend is visualized well with hard data for Hampton Roads, Virginia, by the Hampton Roads Economic Development Alliance.
Chad Matheson, Director of Business Intelligence at HREDA, used Emsi data and Tableau to show the concentration of millennials (19- to 34-year-olds in this case) by occupation and typical education level. We liked this data visualization so much that we wanted to share it here.
A little background on this visualization, courtesy of Matheson:
HREDA created the chart to highlight the young professional and technical workforce in Hampton Roads, defined as the Virginia Beach-Norfolk-Newport News MSA in southeast Virginia. “The underlying motivation,” Matheson says, “was to try to better understand which industries/occupations held a generous critical mass of young professional talent.”
He chose to include 19- to 21-year-olds in his millennial definition in order to capture young workers who have an associate degree or some college but no degree. And to weed out very small fields, he only included occupations with at least 300 jobs (across all ages) in Hampton Roads in 2005.
Applications & Takeaways
One of the neat things that Matheson did with this data viz is layer in filters by median hourly wage, industry, and typical education level. (For the industry filter, he tagged the most common 2-digit NAICS sector that employs each occupation using Emsi’s staffing pattern data.)
Because of these extra layers, you can quickly gauge the concentration of millennial employment in occupations, for example, that pay at least $20 an hour and require a bachelor’s degree (market research analysts, financial analysts, and graphic designers pop to the top). Or the most representative occupations for millennials in manufacturing, professional services, or any other sector.
This is a fantastic example of the power of data visualized in a way that leads to clear, actionable insights.