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.
Requirements- Ph.D. in bioinformatics, computational biology, genomics, statistics, or a related quantitative discipline with 3-5+ years of relevant industry experience
- Self-motivated, hardworking, and adaptable
- Strong foundation in statistics and machine learning, including supervised and unsupervised methods, dimensionality reduction, and model evaluation
- Deep hands-on experience with single-cell analysis frameworks (e.g., Scanpy, Seurat, scVI) and associated workflows across the full analytical lifecycle
- Strong proficiency in Python and R for data analysis, visualization, and pipeline development; Javascript experience is a plus
- Demonstrated experience supporting drug discovery and development programs with computational and bioinformatic analyses
- Proficiency in utilizing AI and large language model-based tools for research acceleration and software development
- Excellent written and verbal communication skills, including the ability to present complex technical work to both computational and non-computational audiences
- Strong team player with a collaborative mindset and a commitment to working in a small, tight-knit, and high-performing team environment
Preferred
- Background in neuroscience, developmental biology, or related areas of disease biology
- Experience in cell therapy research, manufacturing analytics, or related cell-based therapeutic modalities
- Familiarity with spatial transcriptomics platforms (e.g., 10x Visium, Xenium, MERFISH) and integrative multiomics approaches
- Track record of scientific contributions evidenced by peer-reviewed publications, patents, or conference presentations
Benefits
