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# Statistical Programmer

- **Company:** University of Oxford
- **Location:** Oxford, UK
- **Salary:** £39,424.0 - £47,779.0
- **Contract:** Temporary contract
- **Skills:** Big Data, Computer Programming, Databases, Data Cleansing, Data Sharing, Relational Databases, Database Design, PostgreSQL, MySQL, Stata, Information Technology, Data Management
- **Published:** July 27, 2026
- **Apply:** https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form?p_company=10&p_internal_external=E&p_display_in_irish=N&p_process_type=&p_applicant_no=&p_form_profile_detail=&p_display_apply_ind=Y&p_refresh_search=Y&p_recruitment_id=187745

## About the Role

This is an exciting opportunity for an experienced statistical programmer with a strong background in large-scale database management, data linkage, and programming. The appointee will work closely with epidemiologists, statisticians, IT staff, and research coordinators on large prospective epidemiological studies investigating lifestyle, dietary, hormonal, molecular, and genetic factors in relation to cancer and other common non-communicable diseases., You will hold a degree in a numerate subject, such as statistics, mathematics, computer science, or a related discipline, or have equivalent relevant experience. You will have experience managing and manipulating large-scale datasets, strong programming skills in Stata or R, and experience working with relational database management systems, ideally PostgreSQL or MySQL. Experience with linked health data, including NHS data sources, and familiarity with database design would be advantageous.
The post is full-time (although part-time is considered) and fixed term for 2 years. The closing date for applications is noon on 27 August 2026.

## Description

The main responsibilities will include managing, developing, linking, cleaning, and maintaining large research databases, particularly those associated with the EPIC study and EPIC-Oxford cohort. The postholder will process and integrate data from linked health records, questionnaires, laboratory assays, and other sources, and prepare datasets for research projects. Additional duties include managing Biobank databases, supporting sample tracking, maintaining database documentation, and developing reusable statistical programming code. The appointee will work closely with researchers to prepare datasets, conduct data cleaning and analyses, generate tables and figures, and contribute to data management and data-sharing activities across the Unit.


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