The table below provides summary statistics for permanent job vacancies advertised in Reading requiring Data-Driven Decision Making skills. It includes a benchmarking guide to the annual salaries offered in vacancies that cited Data-Driven Decision Making over the 6 months leading up to 2 May 2025, comparing them to the same period in the previous two years.
Data-Driven Decision Making falls under the Processes and Methodologies category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring process or methodology skills in Reading.
Permanent vacancies with a requirement for process or methodology skills
434
1,509
1,579
As % of all permanent jobs advertised in Reading
85.43%
88.30%
97.17%
Number of salaries quoted
234
917
822
10th Percentile
£31,750
£30,000
£31,250
25th Percentile
£43,125
£39,380
£41,250
Median annual salary (50th Percentile)
£62,500
£54,995
£60,000
Median % change year-on-year
+13.65%
-8.34%
-
75th Percentile
£83,750
£70,000
£77,500
90th Percentile
£103,500
£80,000
£92,500
Berkshire median annual salary
£60,000
£54,000
£60,000
% change year-on-year
+11.11%
-10.00%
+3.45%
Data-Driven Decision Making Job Vacancy Trend in Reading
Job postings citing Data-Driven Decision Making as a proportion of all IT jobs advertised in Reading.
Data-Driven Decision Making Salary Trend in Reading
3-month moving average salary quoted in jobs citing Data-Driven Decision Making in Reading.
Data-Driven Decision Making Top 11 Co-occurring Skills and Capabilities in Reading
For the 6 months to 2 May 2025, 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 Reading region with a requirement for Data-Driven Decision Making.
Data-Driven Decision Making Co-occurring Skills and Capabilities in Reading 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:
