Principal Biostatistician – Biomarker
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Job Description
Biostatistician focusing on biomarker studies at Syneos Health. Collaborating on clinical studies and conducting statistical analysis.
Responsibilities:
- Collaborates with representatives from other functions to plan, execute and analyze all biomarker aspects of clinical studies or biomarker studies in the role of the biomarker statistician and assumes the role of project biomarker statistician under guidance of an experienced statistician
- Develops the Biomarker Evaluation Plan for the study as appropriate, ensuring overall consistency within and between projects
- Provides statistical input in clinical development discussions, and usage of AI and ML approaches
- Facilitates the overall organization and coordination of statistical activities regarding biomarker research and development activities for specific studies and projects
- Conduct and design advanced data analysis for genomics and biomarker statistics, including statistical programming, and design complex analysis algorithms
- Assumes responsibility for the production and accuracy of the Biomarker Evaluation Report with respect to statistical deliverables and interpretation of the results
- Works independently at routine and complex statistical questions, modeling and tasks
- Develops and implements standard processes for the analysis of routine (parts of) biomarker assessments
Requirements:
- PhD or MSc in Biostatistics, Statistics or Mathematics, or related field
- Strong communication and interpersonal skills
- Ability to work independently as well as collaboratively, as required
- Minimal supervision required
- Usage of AI and ML approaches
- Previous experience in independently leading biomarker study mandatory
- Previous clinical trial experience, industry experience is preferred
- Strong knowledge on Biomarker evaluation, esp. In immunology and infections, type I diabetes, relevant parameters and underlying biology
- Good knowledge of statistical programming languages including R (Bioconductor package and other relevant R packages for genetic data), Python
- Analysis of high-dimensional data
Benefits:
- Career development and progression
- Supportive and engaged line management
- Technical and therapeutic area training
- Peer recognition and total rewards program
- Inclusive culture
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