The following table provides summary statistics for permanent job vacancies advertised in Canterbury with a requirement for Machine Learning skills. Included is a benchmarking guide to the salaries offered in vacancies that have cited Machine Learning over the 6 months to 23 April 2024 with a comparison to the same period in the previous 2 years.
6 months to 23 Apr 2024
Same period 2023
Same period 2022
Rank
20
-
32
Rank change year-on-year
-
-
-
Permanent jobs citing Machine Learning
2
0
2
As % of all permanent jobs advertised in Canterbury
Machine Learning 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 Canterbury with a requirement for process or methodology skills.
Permanent vacancies with a requirement for process or methodology skills
58
46
144
As % of all permanent jobs advertised in Canterbury
78.38%
95.83%
98.63%
Number of salaries quoted
52
20
67
10th Percentile
£27,965
£30,500
£25,230
25th Percentile
£34,375
£36,688
£37,000
Median annual salary (50th Percentile)
£47,750
£44,800
£46,500
Median % change year-on-year
+6.58%
-3.66%
+24.00%
75th Percentile
£60,313
£58,350
£53,750
90th Percentile
£65,000
£70,790
£56,750
Kent median annual salary
£42,500
£47,500
£45,000
% change year-on-year
-10.53%
+5.56%
+11.80%
Machine Learning Job Vacancy Trend in Canterbury
Job postings citing Machine Learning as a proportion of all IT jobs advertised in Canterbury.
Machine Learning Top 18 Co-occurring Skills and Capabilities in Canterbury
For the 6 months to 23 April 2024, job vacancies citing Machine Learning 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 Canterbury region with a requirement for Machine Learning.
Machine Learning Co-occurring Skills and Capabilities in Canterbury 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:
