Principal RWD Biostatistician

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Offer statistical expertise for clinical development strategies, concept documents, and study protocols.

• Execute statistical evaluations and analyze clinical trial data to aid in decision-making processes.

• Assist in the development of statistical analysis plans (SAPs) and clinical study reports.

• Create and implement statistical as well as machine learning models to facilitate the analysis of clinical study information.

• Write code to construct and utilize analytical models within study analyses, including predictive or exploratory modeling methods as appropriate.

• Utilize statistical methodologies, machine learning, or Bayesian techniques to extract insights from clinical datasets.

• Design and conduct hypothesis testing and exploratory analyses to address clinical development queries.

• Perform statistical analyses using R and/or Python, with SAS utilized where necessary.

• Collaborate primarily with the biostatistics team to produce high-quality analyses for clinical studies.

• Effectively communicate analytical findings and statistical concepts to stakeholders within the study team.

⛳️ Requirements

• Master’s degree in Statistics, Biostatistics, Mathematics, or a related quantitative field. A PhD is preferred but not mandatory.

• Solid statistical and mathematical background with strong logical reasoning capabilities.

• Experience in the industry supporting clinical trials is a plus, though not strictly necessary for candidates with robust quantitative skills.

• Familiarity with clinical or biomedical datasets is beneficial.

• Knowledge of cloud computing (AWS, Microsoft Azure, GCP (Google Cloud Platform)) and big-data environments (SQL, Spark, Databricks, Snowflake) is a plus.

• Proficient in R programming (required); knowledge of Python is also advantageous.

• Understanding of SAS is beneficial, especially for quality control and regulatory outputs, but candidates with strong R/Python skills can quickly learn SAS.

• Familiar with statistical modeling techniques, such as regression, survival analysis, or Bayesian methods.

• Exposure to machine learning techniques is preferred. Basic knowledge of version control systems (e.g., Git) or a willingness to learn quickly is desired.

• Strong analytical and problem-solving skills.

• Exceptional attention to detail and a dedication to quality.

• Ability to work independently and show initiative.

• Effective communication skills and ability to clearly articulate statistical findings.

• Team-oriented mindset with the capability to collaborate effectively within a statistical team environment.

🏝️ Benefits

• At Cytel, we are committed to our employees' success, providing consistent training, development, and support to help them thrive.