Posted 4w ago

Senior Scientist, Bioinformatics

@ Kenai Therapeutics
San Diego, California, United States
HybridFull Time
Responsibilities:design pipelines, analyze data, collaborate teams
Requirements Summary:Ph.D. in bioinformatics, computational biology, genomics, statistics, or related quantitative field with 3–5+ years industry experience; strong statistics and ML foundation; extensive single-cell analysis experience; proficient in Python and R; experience supporting drug discovery; able to use AI/LLM tools; excellent communication; collaborative; adaptable.
Technical Tools Mentioned:Python, R, Scanpy, Seurat, scVI, JavaScript
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Job Description

Kenai Therapeutics is seeking a skilled and versatile computational biologist to join our highly collaborative, multidisciplinary, and dynamic team advancing next-generation allogeneic cell therapies for neurological diseases. As Senior Scientist of Bioinformatics, the ideal candidate will drive computational analysis and pipeline development across CMC and research programs. This candidate brings scientific rigor, deep hands-on expertise in single-cell and multiomics analysis, and a strong foundation in statistics and machine learning to generate actionable insights that inform therapeutic decision-making. This role requires exceptional technical skills, a proven ability to communicate complex findings across scientific disciplines, and a desire to thrive in a small, fast-moving organization where flexibility and initiative are essential.

Key Responsibilities:

  • Design, implement, and maintain scalable, reproducible pipelines for single-cell RNA-seq, spatial transcriptomics, and integrative multiomics data analysis, from raw data through biological interpretation
  • Apply statistical modeling and machine learning approaches to large-scale omics datasets to identify biomarkers, characterize cellular heterogeneity, and aid process development
  • Leverage AI-based tools and platforms to accelerate research workflows, automate analyses, and enhance software development productivity
  • Perform complex data interpretation across modalities (scRNA-seq, genomics, spatial omics, proteomics) and translate findings into actionable insights for programs and leadership
  • Partner closely with manufacturing and research teams to align computational efforts with therapeutic objectives and program priorities
  • Contribute to data infrastructure strategy, supporting robust systems for data storage, integration, traceability, and long-term analytics
  • Communicate results effectively through internal presentations, and cross-functional meetings; distill complex analyses into clear narratives for diverse audiences.