Medical Statistics and Data Scientist

YOU MAKE US MORE

Join Moorfields Eye Hospital NHS Foundation Trust

At Moorfields, people's sight matters-and so do the people who make it possible.

For over 200 years, Moorfields has been at the forefront of ophthalmic care, research, and education. With more than 2,300 dedicated team members and over 700,000 patients seen annually across our City Road site and 22 networked sites, we are proud to be a global centre of excellence.

We're also a vibrant community where kindness, equity and excellence shape every aspect of our work. Whether it's pioneering research through our partnership with UCL Institute of Ophthalmology and Moorfields Biomedical Research Centre or training the next generation of global eye care leaders, we're united by one mission-delivering world-class eye health, sustainably and at scale.

And we're just getting started.

From 2027, we'll move to our brand-new Oriel site in St Pancras, Camden-a state-of-the-art centre that will unite eye care, research, and education under one roof. This groundbreaking facility, developed in partnership with UCL Institute of Ophthalmology and Moorfields Eye Charity, will enable transformative innovation and collaboration like never before.

Could you be part of this future? Make us more.

Job overview

Previous applicants need not apply

The Medical Statistics and Data Scientist will provide statistical and data science expertise to support a diverse portfolio of academic, commercial and grant-funded ophthalmic research studies within the Moorfields Reading Centre and Clinical Research Facility.

The postholder will work closely with clinicians, researchers, data scientists and external collaborators to design statistical analyses, manage research datasets, develop predictive models and contribute to high-quality publications, grant applications and regulatory reporting. The role will also support the development of advanced imaging analysis, artificial intelligence and data-driven research methodologies.

This is an excellent opportunity for an individual with strong analytical skills who is passionate about applying statistics and data science to improve patient care and advance ophthalmic research.

Technical

To independently provide all statistical interpretation, analysis, and modelling for grant funded studies that include highly specialised areas such as developing risk scores, predictive models and linkage of large datasets

Responsible for complex analysis of cross-disciplinary data.

Interest in medical research (e.g. epidemiology, public health) and willingness to apply for grants to self-sustain the position during the fixed term contract.

Experience in statistical modelling including longitudinal data analysis and survival analyses and collaborating with multiple researchers across various institutions

Experience in conducting analysis of observational/real-world medical research data.

Independence and initiative to work unsupervised with excellent attention to detail.

Cross-disciplinary problem-solving and project-management skills.

Ability to assimilate current statistical and mathematical literature on a topic and address investigations accordingly.

Responsible for development of an appropriate research methodology in order to address the research objective; compile and analyse quantitative and qualitative data, prepare reports and present results to summarise main findings and conclusions.

Responsible for interpretation of large amount of data in conjunction with the research team, putting acquired information into context with other clinical tests.

Responsible for the transfer of technical information on statistics to research fellows and students.

Develop and maintain an understanding of a range of specialised data requiring expertise underpinned by theoretical knowledge.

A honorary contract with UCL will be established to ensure that collaborations with UCL is developed.

Management

• Responsible for the supervision of the Research students working within the CRF and R&D, ensuring their training is appropriate for statistical analysis where necessary.
• Undertake training of junior staff where appropriate to facilitate the attainment of core statistics competencies.
• Manage own workload effectively and efficiently, planning and prioritising activities to meet the needs of the service.
• Carry out duties with a high degree of autonomy on a day to day level but appropriately identifying areas requiring further training and support or supervision.
• Attend national and international meetings where…