The PositionJoin our team and drive the future of programmable eRNATM therapeutics and In Vivo CAR-T therapies- where AI-driven biology, targeted delivery systems and next-generation immunotherapy converge to redefine what's possible for patients. As a key member of the Sail Biomedicines Data Science team, the Senior Scientist I will operate at the interface of platform and program, applying data-driven approaches to champion broad platform efforts and hands-on analysis of preclinical datasets to transform the treatment landscape for autoimmune diseases, and beyond.
The ideal candidate will combine strong biological insight with quantitative rigor, applying data-driven approaches to extract actionable understanding from complex preclinical and platform datasets while helping establish scalable computational foundations for future discovery efforts. In addition to supporting in vivo CAR immunology programs, this role will contribute to emerging capabilities in systems modeling, computational protein design, molecular modeling, and AI/ML-enabled therapeutic engineering.
Partnering closely with experimental scientists, you will spearhead efforts to translate platform and program data into actionable understanding of biology, enabling rapid iteration across our therapeutic learning cycle.
Responsibilities - Perform in-depth analysis of preclinical and platform datasets, including immunophenotyping, functional assays, and multi-omics data to support both therapeutic programs and platform development
- Integrate and interpret data across studies and contexts to generate biological insights that inform CAR activity, persistence, immune dynamics and platform-level understanding of our therapeutics
- Collaborate closely with immunology and platform teams to inform experimental design and interpret results
- Work resourcefully with internal/external datasets to contextualize findings and strengthen conclusions
- Apply statistical and systems modeling to develop deeper understanding of product and platform attributes and performance.
- Apply and promote best practices in data structuring, annotation, and metadata usage to enable reliable, scalable and reusable downstream analysis across programs and platform efforts
- Develop and maintain reproducible analysis workflows, with clear documentation and version control (Git) and contribute to a well-organized data environment by following FAIR-aligned practices in day-to-day work
- Communicate findings clearly with collaborators through visualizations, presentations, and written summaries
Qualifications Required:
- Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics or related field
- 3+ years of experience analyzing multifaceted biological datasets in biotech, pharma, or academia
- Firsthand experience working in CAR-T or RNA therapeutics.
- Demonstrated experience applying modeling (statistical, system) to biological data.
- Strong expertise in high-dimensional data analysis (e.g., RNA-seq, single-cell, in vivo studies) with the ability to transform raw data to refined downstream biological interpretations
- Proficiency in Python and/or R, with strong data analysis and visualization skills and a firm grasp of modern statistics (mixed models, Bayesian methods, etc.)
- Experience building reproducible and well-documented analysis workflows (Nextflow, Snakemake) and applying sound data organization and metadata practices
- Demonstrated ability to champion cross-functional efforts in close collaboration with experimental scientists, taking ownership and driving insights even in areas outside your core subject matter expertise
Preferred:
- Computational design of Antibody/VHH/scFv/CAR proteins
- Experience in immunology, cell therapy, or CAR biology, particularly in vivo systems
- Experience integrating complex datasets and cross-study meta-analysis
- Exposure to cloud-based or collaborative data environments
- Track record of impactful scientific contributions (publications or program support)
Salary Range: $130,000 - $170,000
