Senior Scientist I, Computational Biology

• Lead analysis of preclinical research datasets, including immunophenotyping, functional assays, and multi-omics data to support therapeutic development
• Develop, adapt, and benchmark computational and statistical methods to address biological questions where standard workflows are insufficient
• Integrate and interpret data across studies leveraging internal and external resources to contextualize findings, evaluate consistency, and strengthen understanding of our therapeutics
• Partner with experimental scientists to shape experimental design, identify limitations, interpret results, and prioritize follow-up studies.
• Build and maintain reproducible analysis workflows, with clear documentation and version control (Git) with consistent data annotation and metadata practices.
• Communicate findings, uncertainty, and implications with collaborators through effective visualizations, presentations, and written summaries

• Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics, or a related quantitative discipline.
• 3+ years of hands-on computational biology research in biotech, pharma, or academia.
• A record of independently leading substantial computational biology projects, including developing, adapting, and benchmarking analytical methods. Evidence may include methods development, reusable scientific software, publications, or documented contributions to therapeutic research.
• Deep expertise in at least one relevant area, such transcriptomics, multi-omics analysis, or quantitative analysis of preclinical studies, spanning data generation, quality control, methodological choices, and biological interpretation.
• Strong grounding in statistical modeling, with demonstrated ability to address confounding, batch effects, biological versus technical variation, and experimental-design limitations, and to assess uncertainty and sensitivity to analytical choices.
• Strong programming skills in Python and/or R, with experience independently developing and maintaining reproducible, well-documented scientific analysis code and workflows.
• Demonstrated ability to collaborate effectively with experimental scientists, take ownership of scientific questions, be a proactive force driving improvement, and being comfortable developing to contribute beyond your core area of expertise.

• Experience in CAR biology, immunology, cell therapy, or RNA therapeutics.
• Experience integrating heterogeneous datasets across studies or conducting meta-analysis
• Experience with workflow orchestration tools to cloud-based or collaborative data environments
• Track record of impactful scientific contributions (publications or program support)
• Computational protein design and / or structural biology experience a plus

Sail Biomedicines is building a new class of fully programmable medicines by integrating circular RNA (eRNA™), targeted nanoparticle delivery, and advanced computational approaches. Our platform enables the systematic design and optimization of therapies, unlocking new possibilities across immunology and beyond.