Closing date: 25 May 2026
This Macmillan Cancer Support-funded post offers a unique opportunity to work at the National Cancer Audit Collaborating Centre (NATCAN) within the Clinical Effectiveness Unit (CEU) at the Royal College of Surgeons of England (RCSEng). NATCAN is a national centre of excellence dedicated to strengthening NHS cancer services and reducing variation in care. It is the home to all 10 National Cancer Audits in England and Wales. NATCAN is the largest centre evaluating cancer services in the UK, with 45 staff members, employed at the RCSEng or the LSTHM, from a wide range of backgrounds (medicine, statistics, epidemiology, data science, quality improvement, project management).
This post will support a Macmillan funded partnership with NATCAN to
improve understanding of how to:
- Reduce health inequities within cancer treatment and care;
- Support those with cancer and other long-term conditions;
- Reduce unwarranted variation in cancer treatment and care.
The successful candidate will complete a PhD focused on one of the following thematic areas:
- Hub and Spoke model – understanding variation in outcomes between hubs (tertiary centres) and spokes (general hospitals)
- Treatment Attrition – understanding who drops out of treatment and why
- Under-treatment and over/inappropriate treatment – understanding why some people receive less or no treatment, or treatment that differs from clinical guidance
This is a key role in data science and reporting in NATCAN, working closely with senior cancer specialists, clinical fellows, methodologists, data managers, and other multidisciplinary team members. The post holder will develop advanced analytical and research skills. Having large detailed linked datasets provides opportunities to be involved in methodological development and in epidemiological studies assessing the quality of care and answering the most pressing questions about why some cancer patients receive different treatments and outcomes than others. The results of the work will be disseminated as peer-reviewed academic papers, and conference presentations as well as audit reports and their online dashboards. Work of the post holder will also include some of the following: supporting development to improve the efficiency of data analysis and reporting within the centre; working on the data flow into and within NATCAN; data validation; data science processes; automated reporting; state-of-the-art data visualisation and dashboards.
A current Data Scientist in NATCAN says:
“This role provides a fantastic opportunity to be
part of multidisciplinary teams carrying out clinical audit and research with ‘big data’. For this
to drive quality improvement and make a real difference to patients, we need more input
from data scientists to handle the data coming into NATCAN efficiently and analyse and
report on it effectively. My role has been extremely well-supported from academics and
clinicians at the forefront of their fields and has provided me with invaluable opportunities to
develop my data science skills, present at national and international conferences, and
contribute to meaningful improvements for patients with cancer. I cannot recommend this
position highly enough.”
Responsibilities
- Carry out statistical analyses to explore the thematic area using national datasets on hospital care, surgery, chemotherapy and radiotherapy.
- Extract and curate large scale linked clinical datasets ready for analysis using SQL or statistical software
- Develop reusable data pipelines and apply algorithms to derive required variables
- Produce reports, dashboards and data visualisations to support local quality improvement
- Ensure projects comply with information governance policies
- Communicate findings in seminars, conference presentations, reports and academic journals
About you
We are looking for applicants with
- Bachelor Level/ Higher degree in medical statistics, data science, epidemiology, operational research or equivalent academic qualification
- A good understanding of health-related research methods and study designs
- Experience of undertaking analyses using large complex datasets in a statistical package
- Evidence of contributions to written output, preferably peer-reviewed
- Experience of applying information governance principles to health care data