The table below provides summary statistics and salary benchmarking for jobs advertised in Dartford requiring Machine Learning skills. It covers permanent job vacancies from the 6 months leading up to 10 November 2025, with comparisons to the same periods in the previous two years.
Machine Learning 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 Dartford.
Permanent vacancies with a requirement for process or methodology skills
25
53
77
As % of all permanent jobs advertised in Dartford
92.59%
80.30%
97.47%
Number of salaries quoted
19
8
54
10th Percentile
£29,050
£40,625
£26,250
25th Percentile
£30,000
£46,250
£29,563
Median annual salary (50th Percentile)
£40,000
£52,500
£50,000
Median % change year-on-year
-23.81%
+5.00%
+33.33%
75th Percentile
£45,000
£58,750
£58,438
90th Percentile
£50,000
-
£58,750
Kent median annual salary
£40,000
£55,000
£50,000
% change year-on-year
-27.27%
+10.00%
-
Machine Learning Job Vacancy Trend in Dartford
Historical trend showing the proportion of permanent IT job postings citing Machine Learning relative to all permanent IT jobs advertised in Dartford.
Machine Learning Salary Trend in Dartford
Salary distribution trend for jobs in Dartford citing Machine Learning.
Machine Learning Top 10 Co-Occurring Skills & Capabilities in Dartford
For the 6 months to 10 November 2025, job vacancies citing Machine Learning also mentioned the following skills and capabilities in order of popularity.
The figures indicate the absolute number of co-occurrences and as a proportion of all permanent job ads across the Dartford region with a requirement for Machine Learning.
Machine Learning Co-Occurring Skills & Capabilities in Dartford by Category
The following tables expand on the one above by listing co-occurrences grouped by category. They cover the same employment type, locality and period, with up to 20 co-occurrences shown in each category:
