Microsoft Azure Machine Learning (Azure ML) South East> Surrey
The following table provides summary statistics for permanent job vacancies advertised in Surrey with a requirement for Azure Machine Learning skills. Included is a benchmarking guide to the salaries offered in vacancies that have cited Azure Machine Learning over the 6 months to 1 June 2024 with a comparison to the same period in the previous 2 years.
Azure Machine Learning is in the Cloud Services category. The following table is for comparison with the above and provides summary statistics for all permanent job vacancies advertised in Surrey with a requirement for cloud computing skills.
Permanent vacancies with a requirement for cloud computing skills
761
772
1,639
As % of all permanent jobs advertised in Surrey
28.44%
36.83%
45.97%
Number of salaries quoted
577
578
933
10th Percentile
£27,500
£34,750
£30,500
25th Percentile
£41,250
£43,750
£42,500
Median annual salary (50th Percentile)
£55,000
£60,000
£55,000
Median % change year-on-year
-8.33%
+9.09%
-
75th Percentile
£67,500
£81,250
£70,000
90th Percentile
£85,000
£95,000
£81,000
South East median annual salary
£50,000
£56,500
£55,000
% change year-on-year
-11.50%
+2.73%
+4.76%
Azure Machine Learning Job Vacancy Trend in Surrey
Job postings citing Azure Machine Learning as a proportion of all IT jobs advertised in Surrey.
Azure Machine Learning Salary Trend in Surrey
3-month moving average salary quoted in jobs citing Azure Machine Learning in Surrey.
Azure Machine Learning Top 18 Co-occurring Skills and Capabilities in Surrey
For the 6 months to 1 June 2024, job vacancies citing Azure 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 Surrey region with a requirement for Azure Machine Learning.
Azure Machine Learning Co-occurring Skills and Capabilities in Surrey 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:
