Senior Programmer

3 weeks ago

United Kingdom Cytel Full time

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. As a Senior Statistical Programmer 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. As a Senior Statistical Programmer, you will leverage your advanced SAS programming skills and proficiency in CDISC standards. This role can be performed as fully remote.
We believe in applying scientific rigor to reveal the full promise inherent in data.
We believe in collaboration and invite a diversity of perspectives, drawing on a variety of talents to create a wealth of possibilities.
Data analysis and programming:
Write, document, and maintain code in programming languages like R, SAS.
Transform raw data into standardized, analysis-ready datasets.
Perform statistical analysis and generate visualizations from pre-clinical and clinical study data.
Data management and quality:
Organize, manage, and ensure the quality of biomarker data.
Coordinate with external vendors and labs to resolve data issues and reconcile vendor data.
Maintain integrated tracking and inventory logs for biological samples.
Participate in the design and planning of studies related to biomarkers.
Contribute to the development of biomarker strategies and biomarker analysis plans.
Collaborate with stakeholders to define data specifications and requirements.
Here at Cytel we want our employees to succeed and we enable this success through consistent training, development and support. Bachelor’s degree in one of the following fields Statistics, Computer Science, Mathematics, etc.
Proficiency in programming, especially with statistical software like SAS or R, and database languages like SQL.
Experience with statistical analysis, data visualization, and modeling.
Familiarity with analyzing large, complex datasets, such as omics data (e.g.,

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