Senior Scientist, Bioinformatics

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

Qualifications

• 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