Research Data Ops Engineer

A fantastic opportunity has become available for a Research Data Ops Engineer to join Caristo Diagnostics rapidly growing team, based at our Oxford headquarters.

Caristo Diagnostics is a global leader in AI-powered heart disease detection. A spinout from the University of Oxford, Caristo’s award-winning technology is transforming cardiovascular care by identifying hidden heart attack risks before symptoms appear. Backed by leading hospitals and scientists, Caristo is on a mission to save lives through early detection and personalized prevention. For more information, visit

Named first of 7 Technologies That Could Change Heart Healthcare Forevermore by the Robb Report, the CaRi-Heart technology is Caristo’s flagship offering which aids coronary artery disease diagnosis with improved risk prediction. It applies advanced AI algorithms to routine cardiac CT scans to visualize and quantify coronary inflammation, which is the previously invisible root cause of the disease. Multiple patents underpinning CaRi-Heart technologies have been granted in major jurisdictions around the world.

In addition, exceptional validation results showing CaRi-Heart’s ability to aid the prediction of heart attacks have been published in leading medical journals including the Lancet, JACC, European Heart Journal, and Cardiovascular Research. The technology is regulatory-approved for commercial use in the UK, Europe and Australia, and is currently being piloted in several NHS sites. The CaRi-Heart Technology is also a receipt of the NHS AI award, and has been recognised by the British Heart Foundation as a game-changing innovation for preventing cardiovascular disease.

This is an exciting opportunity for Research Data Ops Engineer with a passion for research delivery, to join an Oxford University spin-out and to implement a Data Lake House from the ground up. This role is critical to support the next phase of our medical imaging AI and Analytics research. The role will be onsite building hybrid-cloud/on-premises infrastructure spanning Caristo and Oxford University.

This individual will join a fast-paced and talented research team of 8 individuals to support a variety of data and computing needs. The successful candidate will design and build out a data lake house, whilst being expected to actively contribute to on-going data-centric product research.

• be motivated at the thought of working in an innovative healthcare start-up with a strong collaborative research and operations culture, helping to build a global business that will have material impact on the health and wellbeing of potentially millions of people.
• share the company values of pushing the boundaries, taking ownership, caring for each other and acting with candour and professionalism.

Responsibilities include some or all of the following:

• Design and build a secure Data Lake House infrastructure to support AI and Data Analytics Research
• Manage Cloud/On-premises compute resources to achieve research objectives
• Contribute to MLOps pipeline for translation of Research Algorithms to Product
• Collaborate with researchers, academic partners, product team, and image analysts
• Manage cohorts of test data according to GDPR and other data privacy regulations

• Background in research (academic and/or industry)
• Degree in Physics or Mathematics or related discipline
• Experience with unstructured and structured data pipelines including large image datasets
• Knowledge of modern data warehousing and data lake technologies
• Practical experience with Python, R, and ML frameworks (PyTorch and Tensorflow) and statistical methods
• Linux system administration
• AWS and GCP administration
• Experience with GPU cluster and Linux server administration

• PhD in medical image analysis
• Working knowledge of the DICOM standard, volume reconstruction, 3D rendering techniques, statistical modelling
• Experience with AI model training pipelines and architectures (transformers, diffusion models etc)
• Understanding of fundamental statistical concepts (p-values, effect sizes and confidence intervals)
• Experience with MLOps methodologies
• Experience with version control (e.g. Git Lab, DVC)
• Experience with Data Governance in a regulated industry (GDPR, EU AI Act)
• Experience translating research to product

• Have a can-do attitude
• Have an understanding of the need to balance fast delivery and quality
• Be comfortable in a fast-paced environment and embrace the challenge of changing requirements
• Excellent communication and collaboration skills

• Competitive salary (for Oxford location)
• 25 holidays per year plus bank holidays
• Enhanced pension contribution
• Private medical insurance
• Life insurance
• Cycle-to-work scheme
• Additional benefits for long-service

• Be part of a company at the cutting edge of medical technology, with the potential to save lives and…