Senior Manager, Biostatistics

Cytokinetics; California; On-site; USD 170,000 - 210,000; Full time

Job summary

Cytokinetics in California seeks a Senior Manager of Biostatistics to lead statistical analysis plans for cardiovascular programs, integrating ML approaches to enhance data insights across Phase 1-4 trials.

You will collaborate with clinical teams, contribute to protocol design, analyze complex datasets including high-dimensional and observational data, and support regulatory submissions with clear, regulatory-ready reports.

Qualifications

• PhD or MS in Statistics/Biostatistics required.
• 0-2 years (PhD) or 5+ years (MS) biotech/pharma experience preferred.
• Proficiency in SAS and R required.
• Strong problem-solving, strategic agility, and communication skills essential.

Responsibilities

• Develop statistical analysis plans for clinical programs.
• Contribute to protocol design and study planning.
• Analyze complex datasets including high-dimensional and observational data.
• Support regulatory submissions for Phase 1–4 trials.
• Collaborate cross-functionally with clinical teams and translate analyses into regulatory documents.

Skills

SAS

R

Statistical analysis

Data analysis

Education

PhD in Statistics/Biostatistics

Job description

Role: Senior Manager of Biostatistics, supporting clinical development for cardiovascular therapeutics, integrating statistical expertise with machine learning to enhance data insights. Responsibilities: develop statistical analysis plans, contribute to protocol design, analyze complex datasets (including high-dimensional and observational data), and support regulatory submissions for Phase 1-4 trials. Collaborate cross-functionally with clinical teams, ensuring alignment with trial goals, safety, and efficacy assessments; translate analyses into clear reports and regulatory documents. Requirements: Ph.D. or M.S. in Statistics/Biostatistics; 0-2 years (Ph.D.) or 5+ years (M.S.) biotech/pharma experience; proficiency in SAS/R; strong problem-solving, strategic agility, and communication skills. Preferred: experience working with cross-functional teams, familiarity with ML/AI, ability to communicate complex concepts to non-statisticians, and understanding of drug development principles. High-Value: cardiovascular focus, early to late-stage clinical trials, statistical support for regulatory interactions, emphasis on innovative data analysis techniques including machine learning. Work setup: not specified; likely on-site or hybrid based on location.