Head of Biostatistics and Translational Science

6 days ago

Melbourne, Victoria, Australia beBeeLeader Full time $200,000 - $250,000
Biostatistics Leadership Opportunity

Candidates with a strong background in biostatistics and translational science are sought to lead the design, analysis, and interpretation of preclinical data.

  • Leads the development of statistical strategies for research programs.

Key qualifications include:

  • Ph.D. in Biostatistics with 10+ years of experience with at least 5 years in a leadership role.

The ideal candidate will bring deep expertise in biostatistics, strong publication records, and excellent communication and leadership skills.

Job Responsibilities

Strategic Leadership:

  • Drives CSL’s drug discovery by aligning statistical approaches with scientific and business goals.
  • Defines and implements the biostatistics strategy for discovery and translational research programs.
  • Serves as the statistical thought leader across Research, ensuring best practices in experimental design and data analysis.

Scientific and Technical Oversight:

  • Provides statistical guidance on study design, sample size estimation, and data interpretation for in vitro, in vivo, and omics-based studies.

Team Leadership:

  • Builds and leads high-performing teams of biostatisticians and data analysts.

Portfolio Management:

  • Contributes to the planning, execution, and reporting of projects including non-interventional research studies.
Requirements

• Ph.D. in Biostatistics with 10+ years of experience with at least 5 years in a leadership role.

• Proven track record of applying biostatistics to biological or clinical data within the pharma/biotech sector.

• Expertise in NGS data analysis, systems biology, and multi-omics integration.

• Proficiency in statistical programming e.g. R, SAS, Python.

• Strong publication record and/or contributions to open-source biostatistical tools.

• Excellent communication, leadership, and project management skills.

• Strong external network from academia and/or pharma/biotech sectors.

• Familiarity with FAIR data principles and data governance frameworks.

• Background in translational medicine and drug discovery.

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