Senior Research Scientist, Health Economic Modelling

Accountabilities

- Plan, develop, program, analyze, and report health economic and cost-effectiveness simulation models using R and Excel/VBA.

- Independently build economic models from scratch, ensuring that methodologies, assumptions, calculations, and outputs are robust and appropriately documented.

- Contribute to model conceptualization, analysis plans, interpretation of results, sensitivity analyses, and technical reports for client-facing projects.

- Apply statistical methods relevant to health economics, including parametric survival regression extrapolation, network meta-analysis, and probabilistic sensitivity analysis.

- Evaluate clinical and health economic evidence to identify key drivers of results, methodological limitations, data gaps, and opportunities for improvement.

- Support evidence synthesis and decision-modelling projects across pharmaceutical, biotech, and healthcare engagements.

- Analyze and visualize data using R and other appropriate analytical tools, translating complex findings into clear conclusions for technical and non-technical audiences.

- Prepare high-quality presentations, written documentation, reports, and other study deliverables using tools such as Microsoft Word and PowerPoint.

- Communicate project progress, analytical findings, and recommendations clearly with internal teams and external stakeholders.

- Manage assigned project components, timelines, priorities, and deliverables while working independently and collaboratively within multidisciplinary teams.

- Contribute to a culture of knowledge sharing by supporting colleagues, exchanging modelling expertise, and staying current with developments in health economics and statistical methods.

Requirements

- Master’s degree in health economics, statistics, or a related quantitative discipline.

- At least 4 years of relevant professional experience, ideally within a consulting environment supporting pharmaceutical, biotech, healthcare, or related clients.

- Strong professional experience in health economics and outcomes research, with a solid understanding of pharmaceutical markets and drug reimbursement processes.

- Proven ability to program cost-effectiveness and health economic simulation models in R, including developing models independently from scratch.

- Strong Excel and VBA programming skills, with experience planning, implementing, analyzing, and reporting Excel-based economic models.

- Applied knowledge of statistical methods used in health economics, including parametric survival regression model extrapolation, network meta-analysis, and probabilistic sensitivity analysis.

- Strong analytical reasoning and problem-solving skills, with the ability to critically evaluate studies, identify methodological or data gaps, and develop appropriate solutions.

- Proficiency in R for health economic modelling, data analysis, and visualization, along with experience using Git/GitHub or comparable version-control tools.

- Excellent written and verbal communication skills, with the ability to explain technical results clearly to both specialist and non-specialist audiences.

- Strong organizational and time-management abilities, with the capacity to manage multiple priorities and deliver high-quality work within deadlines.

- Collaborative, proactive, and self-directed approach, combined with a willingness to learn and share knowledge.

- Experience with Python, C++, Bayesian statistics, advanced modelling techniques, or indirect treatment comparisons such as network meta-analysis, matching-adjusted indirect comparison, and simulated treatment comparison is advantageous.

- Familiarity with R packages such as hesim, shiny, or Rcpp is a plus.

Benefits

- Opportunity to work on innovative health economics, evidence synthesis, and decision-modelling projects with pharmaceutical, biotech, and healthcare clients.

- Collaboration with a highly specialized international team of health economists, statisticians, and researchers.

- Exposure to methodologically innovative projects and advanced approaches to health economic modelling.

- Strong opportunities for professional development and expanding expertise across HEOR, statistical modelling, evidence synthesis, and decision analysis.

- Collaborative environment that encourages knowledge sharing, technical ownership, and continuous learning.

- Opportunity to contribute to research and analyses that support healthcare and treatment decision-making.

- Remote working opportunity in the United Kingdom.

- Dynamic environment combining the pace and innovation of a growing organization with the resources and stability of an established global business.

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