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Cytel

Principal RWD Biostatistician FSP

Posted 9 Days Ago
Be an Early Applicant
In-Office or Remote
2 Locations
Expert/Leader
In-Office or Remote
2 Locations
Expert/Leader
Lead statistical input and analyses for clinical development, design SAPs, apply statistical, Bayesian and machine learning methods, write R/Python code, and communicate results to stakeholders while collaborating within a biostatistics team.
The summary above was generated by AI
Who Are You? 
An experienced Principal Biostatistician with a passion for clinical development and analysis, adept at utilizing advanced statistical methods, you will lead studies across your region. You are excited and enthusiastic, motivate your teams to do great work and collaborate easily with your clients. You never settle for what is, but always push clinical development forward to what it could be. You motivate others to do the same.  

 
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.
 
Responsibilities

As a Principal Biostatistician, your responsibilities will include:

  • Provide statistical input into clinical development plans, concept sheets, and study protocols.
  • Perform statistical analyses and interpret clinical trial data to support decision making.
  • Contribute to the preparation of statistical analysis plans (SAPs) and clinical study reports.
  • Develop and implement statistical and machine learning models to support analysis of clinical study data.
  • Write code to build and apply analytical models within study analyses, including predictive or exploratory modelling approaches where appropriate.
  • Apply statistical techniques, machine learning, or Bayesian methods to uncover insights in clinical datasets.
  • Design and perform hypothesis testing and exploratory analyses to support clinical development questions.
  • Conduct statistical analyses using R and/or Python, with SAS used where required.
  • Work primarily within the biostatistics team to deliver high-quality analyses for clinical studies.
  • Clearly communicate analytical results and statistical concepts to stakeholders within the study team.
     
Qualifications

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:

  • Master’s degree in Statistics, Biostatistics, Mathematics, or a related quantitative discipline. PhD preferred but not required
  • Strong statistical and mathematical foundation with excellent logical reasoning skills
  • Industry experience supporting clinical trials is beneficial but not strictly required for candidates with strong quantitative backgrounds
  • Experience working with clinical or biomedical datasets is advantageous
  • Familiarity with cloud computing (AWS, Microsoft Azure, GCP (Google Cloud Platform)) and big-data environment (SQL, Spark, Databricks, Snowflake) – nice to have or bonus
  • Programming experience in R (required); Python is also beneficial.
  • SAS knowledge is advantageous, particularly for QC and regulatory outputs, but candidates with strong R/Python skills should be able to learn SAS quickly.
  • Familiarity with statistical modelling techniques, including regression, survival analysis, or Bayesian methods.
  • Exposure to machine learning approaches is desirable. Basic familiarity with version control systems (e.g., Git) or willingness to learn quickly.
  • Strong analytical and problem-solving ability.
  • High attention to detail and commitment to quality.
  • Ability to work independently and demonstrate initiative.
  • Strong communication skills and ability to explain statistical findings clearly.
  • Collaborative mindset and ability to work effectively within a statistical team environment.
     

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