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The Associate Director, Research Biostatistics provides strategic and scientific statistical leadership across CSL Research programs and translational science initiatives, partnering with multidisciplinary teams to design studies, analyse complex research datasets, and generate decision-relevant evidence that supports project and portfolio progression. The role remains hands-on, contributing directly to study design, statistical analysis, innovative methodology development, and evidence-generation strategies that support scientific and portfolio decision-making across discovery, translational, and early research programs.
Key Responsibilities
Provide strategic statistical leadership and methodological oversight across discovery, translational, and early research programs, ensuring robust study design, analysis, interpretation, and project decision support.
Lead and perform complex statistical analyses across preclinical, translational, biomarker, imaging, omics, and human research datasets using advanced methodologies such as Bayesian methods, causal inference, longitudinal modelling, and machine learning.
Develop and apply innovative statistical methods, reproducible analytical workflows, and statistical programming solutions, particularly in R and related platforms.
Support biomarker identification, evaluation, and validation activities, contributing to translational evidence-generation strategies that strengthen research and portfolio decisions.
Translate complex scientific data into actionable insights that support target evaluation, candidate selection, project progression, portfolio prioritisation, and probability-of-success assessments.
Collaborate with Translational Bioinformatics, Global Biometrics, Data Management, PK/PD, and other quantitative functions, applying state-of-the-art statistical methodologies to address scientific challenges.
Contribute to scientific publications, ethics submissions, external collaborations, and scientific communications.
Mentor and develop statisticians, scientists, contractors, and interns, providing scientific leadership and fostering a culture of excellence, collaboration, and continuous learning.
Champion data-driven decision making, promote statistical best practices, and deliver training to strengthen analytical capability across the organisation.
Establish and manage relationships with external collaborators, academic partners, CROs, consultants, and technology providers, ensuring delivery of high-quality scientific outcomes.
Your Profile
PhD in Statistics, Biostatistics, or equivalent experience.
8+ years of experience applying statistics in a pre-clinical pharmaceutical, biotechnology, healthcare, or biomedical research environment, supporting discovery, translational, biomarker, or early development programs.
Demonstrated track record in developing and applying advanced statistical methodologies for biological, translational, biomarker, omics, imaging, or related scientific data.
Proven experience with modern statistical programming, reproducible analysis workflows, and quantitative computing platforms, particularly R and related technologies.
Evidence of scientific contribution through publications, conference presentations, methodological innovations, or development of analytical tools and platforms.
