As a Principal Biostatistician, your responsibilities will include:
- Lead and contribute to advanced real-world evidence (RWE) analyses using large-scale real-world data (RWD) to support clinical development, regulatory strategy, HEOR, and payer decision-making.
- Design observational studies and target trial emulations leveraging diverse data sources including EHR (Electronic Health Record), claims, registries, genomics, and digital health data.
- Apply modern causal inference and statistical learning methods (e.g., propensity score techniques, inverse probability weighting, survival and longitudinal models, representation learning) to address confounding, bias, and missing data.
- Develop and deploy machine learning pipelines for prediction, patient stratification, phenotyping, and NLP (Natural Language Processing) on structured and unstructured healthcare data.
- Integrate AI/ML outputs with traditional statistical frameworks to ensure interpretability, scientific rigor, and regulatory readiness.
- Build scalable, reproducible analytical workflows in Python and/or R, following best practices in software engineering, documentation, and quality control.
- Collaborate closely with clinical scientists, epidemiologists, data engineers, and HEOR partners to define fit-for-purpose analytical strategies.
- Translate complex quantitative results into actionable insights for technical and non-technical stakeholders.
- Contribute to governance readiness, regulatory submissions, audits, and scientific dissemination.
- Deliver high-quality analytical outputs within agreed timelines in a matrixed, global 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+ years of relevant industry experience. - Strong grounding in mathematical statistics, probability, and statistical modeling.
- Demonstrated experience applying machine learning or AI methods to large or high-dimensional datasets.
- Proficiency in Python and/or R; familiarity with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow) preferred.
- Solid understanding of causal inference and observational study design.
- Experience working with large-scale real-world data.
- Strong software engineering mindset, including reproducibility, version control, and documentation.
- Excellent communication skills and ability to collaborate effectively in cross-functional, global teams
- Experience with healthcare RWD (claims, EHR, OMOP/CDM, registries).
- Familiarity with cloud or big-data environments (SQL, Spark, Databricks, AWS, Azure, GCP).
- 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.
Skills Required
- Master's degree in statistics or related discipline
- 9+ years supporting clinical trials in the Pharmaceutical or Biotechnology industry
- SAS programming skills
- Knowledge of R programming
- Ph.D. strongly desired
Cytel Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cytel and has not been reviewed or approved by Cytel.
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Healthcare Strength — Health coverage is described as comprehensive, spanning medical, dental, vision, life and disability, with FSAs/HSAs also available. Plan quality is often characterized as good to excellent, which lifts the perceived value of the overall package.
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Retirement Support — A 401(k) with employer match is consistently part of the benefits package. The plan is also characterized as well managed, contributing to a sense of baseline retirement support.
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Fair & Transparent Compensation — Overall pay is characterized as decent-to-good and broadly competitive in parts of the business, with stronger alignment noted in senior technical tracks like biostatistics and programming. The total package is often framed as respectable rather than premium.
Cytel Insights
What We Do
Cytel enables decision-makers in the life sciences to unlock the full potential of their products. From navigating uncertainty to proving value, Cytel’s 30 years of global expertise in consulting, data-driven analytics, and industry-leading software helps biotech and pharmaceutical companies transform intelligence into confident decisions. We have an uncompromising commitment to scientific rigor and high standards of operational excellence, which are channeled through our locations in North America, Europe, the United Kingdom, and Asia. Together, we enable our clients to deliver the therapies that propel humanity forward. Cytel employs a range of data science tools from biostatistics to machine learning to help executives in the life-sciences to make confident decisions powered by data. We are probably best known for being leaders in the field of adaptive clinical trial design, a subset of trial design that uses interim looks to enhance the patient safety and commercial value of pharmaceutical products. We also have specialists in Bayesian statistics, real world evidence, artificial intelligence, health economics, and a number of other research fields to ensure that academic and scientific findings can have impact on industry quickly and seamlessly. www.cytel.com
