What are the growing, high-paying jobs in your region? This tutorial will give you the framework for finding jobs with a strong local outlook. We’ll focus on wages and growth here, but you can use this workflow with many other variables to fit your needs. In this example we’ll find hot jobs in the Liverpool.
- From the home page click Research Occupations
- Click Occupation Table
- Under “Select Occupations” click All Available
- Under “Select a Region” enter your region (we’ll use Liverpool here)
- Under “Select the data you would like to display” select Custom Data Selection
- Select Job change, % Job change and Median Hourly Earnings
- Click Run
You now have a table listing all occupations, with Liverpool specific job counts and wages. Now we’ll sort and filter this list to bring high wage, high growth jobs to the top.
- In the left-hand sidebar options under “Timeframe,” select 2015 – 20120 (or whatever years you’d like to view the data for)
- Under “Class of Worker” select Employees and Proprietors
- Scroll to the bottom of the table to find the Liverpool average 2015-2020% Change and Median Hourly Earnings. In this case the regional average growth is 3% and the regional average earnings are £12.62/hr. We’ll focus on jobs that are growing faster and paying higher than average.
- Click Filter at the top of the table
- In the first menu bar select Median Hourly Earnings
- In the second menu, select greater than or equal to
- In the last menu, enter 12.62 (£12.62/hr or the average Median Hourly Wage we found at the bottom of the table)
- Click +Add Filter, and repeat the above steps to add the following filters:
- AND >> 2014 – 2018 % Change >> greater than or equal to >> 3
- AND >> 2014 Jobs >> greater than or equal to >> 200 (this is to weed out smaller occupations that have added a handful of jobs and therefore have a high Change %)
- Click Apply
You now have a list of occupations that pay above average, are growing faster than average, and employ at least 200 people. You can further refine the list with more filters, or sort the results by clicking on the different column headers.