So you want to be a Data Viz Wizard? A guide for anyone interested in data visualization as a career.
The Data Visualization Society (DVS) conducted its 2022 State of the Industry (SOTI) survey, with 1,568 visualizers sharing their perspectives on experience, salary, demographics, and roles. We transformed this survey into an interactive career tool, allowing users to explore salary variations and understand the daily lives of data visualizers across different tasks and stages of the process. check out more about the survey
First, where are Data Visualizers?
Select a role to see where in the world they are, and their average income level.
A majority of survey participant identify as "Employee", and are found throughout the world!. As a freelancer, you can earn up to 120,000 USD per year in North America and europe. But as an Employee, you are ‘better’ working in North America than Europe.
Lets visualize income of a data visualizer.
How much each role gets paid depends on education, background, gender, and the amount of time they can work. Choose factors of gender, role, and education level and see how much you might expect to make in the industry.
What are the most common tools used in Data Viz?
Most data visualizers don't say what they studied for their degrees, but rather, their most used tools. Depending on your desired role, what tools are the most popular? Least popular? Below, you can see the percentage of users in each role who use each tool. By clicking any row or column label to sort, you can toggle sort orders and see what tools are the most or least used, keep clicking to toggle sort orders. Click bubble to show annotations.
To our surprise, Excel is the most widely used tool across all roles, especially for employees. Likewise, D3.js is not the most popular tool. This gives new perspective to what future data visualizers should spend their time learning.
Finally, you're probably wondering, how much time should I expect to dedicate to certain aspects of visualization?
Select a role to explore, on average (hours) how long to expect!
Hobbyists, employees, and freelancers spend most of their time producing the visualization. But visualizers in academia spend most of their time preparing the data and analyzing the data. So if you are mostly interested in creating visualizations, academia is probably not the best choice for you.