The table below provides summary statistics and salary benchmarking for jobs advertised in Peterborough requiring Data Mining skills. It covers vacancies from the 6 months leading up to 3 September 2025, with comparisons to the same periods in the previous two years.
6 months to 3 Sep 2025
Same period 2024
Same period 2023
Rank
29
-
-
Rank change year-on-year
-
-
-
Permanent jobs citing Data Mining
1
0
0
As % of all permanent jobs advertised in Peterborough
Data Mining falls under the Databases and Business Intelligence category. For comparison with the information above, the following table provides summary statistics for all permanent job vacancies requiring database or business intelligence skills in Peterborough.
Permanent vacancies with a requirement for database or business intelligence skills
34
16
13
As % of all permanent jobs advertised in Peterborough
22.82%
6.93%
14.94%
Number of salaries quoted
26
10
11
10th Percentile
-
-
£39,000
25th Percentile
£40,000
£29,000
£46,625
Median annual salary (50th Percentile)
£47,500
£40,000
£55,000
Median % change year-on-year
+18.75%
-27.27%
+15.79%
75th Percentile
£57,500
£57,500
£57,500
90th Percentile
£83,738
£106,392
-
Cambridgeshire median annual salary
£35,000
£47,500
£60,000
% change year-on-year
-26.32%
-20.83%
+9.09%
Data Mining Job Vacancy Trend in Peterborough
Job postings citing Data Mining as a proportion of all IT jobs advertised in Peterborough.
Data Mining Salary Trend in Peterborough
Salary distribution trend for jobs in Peterborough citing Data Mining.
Data Mining Top 12 Co-occurring Skills and Capabilities in Peterborough
For the 6 months to 3 September 2025, job vacancies citing Data Mining 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 Peterborough region with a requirement for Data Mining.
Data Mining Co-occurring Skills and Capabilities in Peterborough 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:
