Operational Researcher
Role summary by JobGrid
Operational Researcher at HEOR in Cardiff, United Kingdom is a hybrid Mid role in IT / Data Science & ML. JobGrid normalizes the role facts from the source payload and leaves the employer description separate from the publisher value copy. No salary is listed in the payload, and JobGrid sends candidates to the original public application page with non-personal referral parameters.
- Source posted on 2026-06-05 and last checked on 2026-06-08.
- Original job text is in English; JobGrid keeps the publisher value copy in English as well.
- Comparable classification: IT / Data Science & ML, Mid level, hybrid in Cardiff, United Kingdom.
- The employer application path goes to the original public application page; JobGrid appends non-personal referral parameters.
The Operational Research Group - who we are and what we do!
We are a small, specialist team within HEOR sitting at the intersection of mathematical modelling, data science, and health economics. Our work is genuinely unusual: we build novel quantitative solutions to complex problems in healthcare. We are looking for an innovative problem solver - if you enjoy tackling complex problems and creating innovative solutions – then our operational research group (ORG) could be the place for you to develop your career.
We focus on three key areas:
- Deliver innovative, rigorous solutions to client challenges
- Develop new modelling paradigms and challenging the field to think differently
- Drive quality and efficiency across HEOR through new analytical tools, automation, and data-driven decision-making
We work with differential equations, optimisation algorithms, simulation frameworks, and bespoke software, applied to real decisions in drug development, value demonstration, and healthcare delivery.
You’ll work across a varied portfolio of projects: some client-facing (building models that underpin major healthcare decisions), some internal (designing tools that improve how HEOR operates), and some genuinely novel (developing new methodological approaches and contributing to published thought leadership).
Day to day, you might be:
- Translating a complex clinical or economic decision problem into a mathematical or computational model
- Building R or Python backends and R Shiny frontends for client-facing decision tools
- Applying optimisation techniques and data visualisation to communicate solutions to non-technical audiences
- Collaborating with economists, epidemiologists, and clinicians to define and solve problems across therapy areas
- Support the redesign how we model diseases using AI
- Developing AI agents
- Contributing to proposals, publications, and conference presentations that push HEOR’s methodological frontier
- Developing training resources and analytical frameworks that raise the technical bar across HEOR