Senior Principal Biostatistician

Role Summary

Senior Principal Biostatistician position located onsite in Cambridge, MA. Focus on optimizing data-driven decision-making within the Quantitative Sciences Drug Development function, utilizing clinical study data along with other internal and external data sources.

Responsibilities

• Advanced Modeling & Simulation: Develop and apply sophisticated models to optimize study design, analyze complex datasets, and enhance predictive capabilities.
• Innovative Analytical Methods: Explore and implement novel statistical techniques such as Bayesian modeling, statistical learning, machine learning, and causal inference.
• Rapid-Response Analyses: Conduct flexible, rapid-response analyses to address emerging scientific and regulatory questions.
• Cross-Functional Collaboration: Work closely with Biostatistics, Pharmacometrics, Statistical Programming, and drug development teams to enhance study design, data interpretation, and evidence generation strategies.
• Problem Identification and Solution Development: Identify recurring problems and use a combination of reproducible research techniques and tool development to provide scalable, reusable solutions.
• Quantitative Science Education: Contribute to internal education and awareness efforts in quantitative science.
• External Collaboration: Collaborate with regulatory, academic, and industry partners to advance drug development science through innovative quantitative approaches.
• Scientific Dissemination: Publish in peer-reviewed journals, organize sessions at professional conferences, and contribute to cross-industry workstreams and external scientific working groups.

Qualifications

• Essential Requirements: PhD in statistics, biostatistics, data science or another related field with 3+ years’ experience preferred
• Knowledge in relevant quantitative approaches
• Fluent English (oral and written)
• Strong communication and presentation skills

Skills

• Statistical modeling
• Bayesian methods
• Machine learning and causal inference
• Data visualization and communication
• Cross-functional collaboration

Education

• PhD in statistics, biostatistics, data science or related field

Additional Requirements

• Onsite presence in Cambridge, MA; remote work not available