Operational Researcher
Resumo da vaga pela JobGrid
Operational Researcher at HEOR in Bicester, United Kingdom, is listed as a hybrid, Mid-level role in IT / Data Science & ML. JobGrid normalizes the structured role facts for comparison, keeps the original public application path, and the listing was posted on 2026-06-05 and last checked on 2026-06-08.
- Hybrid role in Bicester, United Kingdom, for HEOR.
- Mid-level position in the IT category, subcategorized as Data Science & ML.
- No salary or employment type is provided in the payload.
- JobGrid routes candidates to the original public application page with 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