Role overview
About the job
We are looking for a statistician with a strong interest in non‑randomized study designs to join our Biometrics and Real World Data (RWD) team. In this role, you will work on studies that sit outside traditional randomized controlled trials. These include observational studies, quasi experimental designs such as pragmatic studies, and single arm studies. You will analyze data generated in real world settings, including digital health tools, registries and emerging evidence platforms, where methodological rigor must be balanced with operational feasibility.
You will contribute to study design, statistical planning and analysis, identifying sources of bias and confounding, and applying appropriate analytical approaches that support fit for purpose conclusions. You will collaborate closely with clinical, data science and regulatory teams to ensure that statistical deliverables are robust, transparent and aligned with both scientific and business objectives. You may also contribute to the evaluation and validation of digital health tools, including predictive and AI based algorithms, in real world or clinical study settings.
You will bring experience with real world data workflows such as data quality assessment, documentation and exploratory analysis. Familiarity with frameworks like the target trial approach, validation of predictive algorithms, high dimensional data or federated learning is considered an advantage.
What you'll work on
- Providing statistical input into protocols and statistical analysis plans for non‑randomized studies.
- Developing and maintaining statistical documents according to internal standards.
- Working with cross functional teams to integrate statistical considerations throughout the study lifecycle.