The following table provides summary statistics for permanent job vacancies advertised in Chester with a requirement for Data-Driven Decision Making skills. Included is a benchmarking guide to the salaries offered in vacancies that have cited Data-Driven Decision Making over the 6 months to 3 May 2024 with a comparison to the same period in the previous 2 years.
Data-Driven Decision Making is in the Processes and Methodologies category. The following table is for comparison with the above and provides summary statistics for all permanent job vacancies advertised in Chester with a requirement for process or methodology skills.
Permanent vacancies with a requirement for process or methodology skills
159
212
130
As % of all permanent jobs advertised in Chester
74.65%
99.07%
95.59%
Number of salaries quoted
135
93
68
10th Percentile
£26,350
£22,600
£30,275
25th Percentile
£31,875
£25,420
£35,000
Median annual salary (50th Percentile)
£47,500
£40,000
£46,250
Median % change year-on-year
+18.75%
-13.51%
+8.82%
75th Percentile
£62,500
£60,899
£54,688
90th Percentile
£67,500
£75,000
£65,000
Cheshire median annual salary
£47,500
£50,000
£47,500
% change year-on-year
-5.00%
+5.26%
+5.56%
Data-Driven Decision Making Job Vacancy Trend in Chester
Job postings citing Data-Driven Decision Making as a proportion of all IT jobs advertised in Chester.
Data-Driven Decision Making Salary Trend in Chester
3-month moving average salary quoted in jobs citing Data-Driven Decision Making in Chester.
Data-Driven Decision Making Top 21 Co-occurring Skills and Capabilities in Chester
For the 6 months to 3 May 2024, job vacancies citing Data-Driven Decision Making also mentioned the following skills and capabilities in order of popularity.
The figures indicate the absolute number co-occurrences and as a proportion of all permanent job ads across the Chester region with a requirement for Data-Driven Decision Making.
Data-Driven Decision Making Co-occurring Skills and Capabilities in Chester by Category
The follow tables expand on the table above by listing co-occurrences grouped by category.
The same employment type, locality and period is covered with up to 20 co-occurrences shown in each of the following categories:
