Associate Director, Research Biostatistics

CSL Vifor; Waltham (MA); On-site; USD 180,000 - 240,000; Full time

Job summary

CSL Vifor is seeking an Associate Director of Research Biostatistics to provide strategic statistical leadership across CSL Research programs from discovery to early development. You will contribute hands-on to study design, analyses, and evidence-generation strategies, applying Bayesian methods, causal inference, and machine learning where appropriate.

The role requires deep statistical expertise, collaboration with Translational Bioinformatics and Global Biometrics, and mentoring of junior

Qualifications

• PhD in Statistics, Biostatistics, or equivalent experience.
• 8+ years of experience applying statistics in pre-clinical/pharmaceutical/biomedical settings.
• Demonstrated track record in advanced statistical methodologies.

Responsibilities

• Provide strategic statistical leadership across discovery, translational, and early research programs.
• Lead and perform complex statistical analyses across diverse datasets.
• Develop innovative statistical methods and reproducible workflows.
• Support biomarker identification and translational evidence-generation.
• Translate complex data into actionable insights for portfolio decisions.
• Collaborate with cross-functional quantitative teams.
• Contribute to scientific publications and external collaborations.
• Mentor statisticians, scientists, and interns in statistical best practices.
• Champion data-driven decision making and statistical training.

Skills

Strategic leadership

Bayesian methods

Causal inference

Longitudinal modelling

Machine learning

R programming

Statistical programming

Mentoring

Data-driven decisions

Education

PhD in Statistics/Biostatistics

Tools

R

Job description

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.