The following table provides summary statistics for permanent job vacancies advertised in Oxford with a requirement for NumPy skills. Included is a benchmarking guide to the salaries offered in vacancies that have cited NumPy over the 6 months to 25 April 2024 with a comparison to the same period in the previous 2 years.
NumPy is in the Software Libraries and Frameworks category. The following table is for comparison with the above and provides summary statistics for all permanent job vacancies advertised in Oxford with a requirement for technical specification, industry standards, software libraries and framework skills.
Permanent vacancies with a requirement for technical specification, industry standards, software libraries and framework skills
122
82
179
As % of all permanent jobs advertised in Oxford
18.65%
17.12%
35.59%
Number of salaries quoted
111
66
132
10th Percentile
£31,250
£41,250
£32,500
25th Percentile
£41,250
£45,000
£50,000
Median annual salary (50th Percentile)
£52,500
£55,000
£62,500
Median % change year-on-year
-4.55%
-12.00%
+25.00%
75th Percentile
£64,250
£69,000
£68,750
90th Percentile
£73,750
£79,375
£80,000
Oxfordshire median annual salary
£52,500
£55,000
£57,500
% change year-on-year
-4.55%
-4.35%
+15.00%
NumPy Job Vacancy Trend in Oxford
Job postings citing NumPy as a proportion of all IT jobs advertised in Oxford.
NumPy Salary Trend in Oxford
3-month moving average salary quoted in jobs citing NumPy in Oxford.
NumPy Salary Histogram in Oxford
Salary distribution for jobs citing NumPy in Oxford over the 6 months to 25 April 2024.
NumPy Top 18 Co-occurring Skills and Capabilities in Oxford
For the 6 months to 25 April 2024, job vacancies citing NumPy 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 Oxford region with a requirement for NumPy.
NumPy Co-occurring Skills and Capabilities in Oxford 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:
