Principal RWE Biostatistician FSP
At a glance
Senior Data Science role at Cytel. Remote, United Kingdom · full-time · no salary stated · we estimate £81,900–£111,875 across the United Kingdom.
Cytel has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Lead real-world data analyses that guide clinical development, regulatory planning, health economics and payer decisions
- Review analysis plans for observational research and target trial emulations using varied healthcare data
- Use causal inference and statistical learning to address bias, confounding and missing information
- Combine machine learning results with established statistical methods to make findings interpretable and suitable for regulatory use
- Work with clinical and data teams to set analysis approaches, explain findings, and support submissions, audits and publications
What you bring
- A doctorate in a quantitative discipline, or a master’s degree with at least three years of relevant industry experience
- Strong knowledge of mathematical statistics, probability and statistical modeling, plus working ability in SAS and R
- A sound grasp of causal inference and observational study design, with experience using large real-world healthcare datasets
Who this fits
This suits a senior biostatistician who can lead real-world evidence studies and communicate results to both technical and non-technical audiences. You’ll work remotely from the United Kingdom, embedded with one pharmaceutical client and supported by Cytel.
From the employer
Sponsor-dedicated: Working fully embedded within one of our pharmaceutical clients, with the support of Cytel right behind you, you'll be at the heart of our client's innovation. You will be dedicated to one of our global pharmaceutical clients; a company that is driving the next generation of patient treatment, where individuals are empowered to work with autonomy and ownership. This is an exciting time to be a part of this new program.
As an RWE Biostatistician, your responsibilities will include:
- Lead and support advanced RWE analyses using large-scale RWD to inform clinical development, regulatory strategy, HEOR, and payer decisions.
- Review statistical analysis plans and provide input for observational studies and target trial emulations using diverse data sources, including EHRs, claims, registries, genomics, and digital health data.
- Apply causal inference and statistical learning methods, such as propensity scores, inverse probability weighting, survival and longitudinal models, and representation learning, to address confounding, bias, and missing data.
- Combine AI/ML outputs with traditional statistical approaches to support interpretability, scientific rigor, and regulatory readiness.
- Collaborate with clinical scientists, epidemiologists, data engineers, and HEOR partners to define fit-for-purpose analytical strategies.
- Translate complex quantitative findings into actionable insights for technical and non-technical stakeholders.
- Support governance readiness, regulatory submissions, audits, and scientific dissemination.
- Deliver high-quality analytical outputs on agreed timelines within a global, matrixed FSP environment.
Here at Cytel we want our employees to succeed, and we enable this success through consistent training, development and support. To be successful in this position you will have:
- PhD in Statistics, Applied Mathematics, Data Science, or related quantitative field or MS with 3-5+ years of relevant industry experience.
- Strong grounding in mathematical statistics, probability, and statistical modeling.
- Proficiency in Statistical programming languages including SAS and R
- Solid understanding of causal inference and observational study design.
- Excellent communication skills and ability to collaborate effectively in cross functional, global teams.
- Experience with large-scale real-world data (administrative claims, EHR, OMOP/CDM, registries).
- Experience with Bayesian modeling or probabilistic machine learning.
- Publications or applied research in ML + healthcare or RWE.
- Interest in translating academic ML into real-world, regulatory-grade analytics.