Principal Scientist - Computational Cancer Immunology

Bristol Myers Squibb • Needham, MA

2d • $166,770 - $202,086

About The Position

Bristol Myers Squibb seeks a computational biologist with deep expertise in single-cell and spatial transcriptomics to serve as the scientific lead for single-cell and spatial analysis across its discovery cancer immunology portfolio within the Oncology team in Informatics and Predictive Sciences (IPS). The role applies computational, machine-learning, and advanced statistical methods to high-dimensional patient and preclinical data to resolve cellular composition, cell states, and spatial organization of the tumor microenvironment, generate and evaluate therapeutic hypotheses, and identify and validate targets.

This is a hands-on individual-contributor position. The scientist will work closely with biologists, translational scientists, and computational biologists, shaping experimental design and integrating molecular and clinical data to support discovery programs from target identification through candidate selection. The role also contributes reusable analytical workflows and methods, communicates scientific findings, and provides mentorship and technical guidance to junior scientists and interns.

Requirements

• Bachelor's degree with 8 or more years of academic or industry experience, master's degree with 6 or more years of experience, or PhD with 4 or more years of experience in computational biology, bioinformatics, computational cancer immunology, or a related field.
• Demonstrated depth in single-cell transcriptomics and a track record of independently delivering scRNA-seq analyses from raw data through biological interpretation.
• Hands-on experience with spatial transcriptomics data from one or more commercial platforms.
• Advanced hands-on knowledge of at least one high-level programming language, such as R or Python, and fluency in associated single-cell and spatial ecosystems such as Seurat, Bioconductor, Scanpy, or Squidpy.
• Reproducible research experience, including version control and workflow management.
• Strong statistical foundation, including experience with experimental design and analysis of nested, repeated-measures, or otherwise non-independent data.
• Track record, such as scientific publications, of driving and advancing research projects or programs using computational approaches.
• Experience supporting drug discovery programs and understanding how computational findings inform target identification, validation, and candidate progression decisions.
• Demonstrated ability to influence, align, and deliver within cross-functional matrix teams without formal authority.
• Strong oral and written communication skills, including the ability to convey complex quantitative results to non-computational audiences.

Nice To Haves

• PhD from a recognized institution in a quantitative field such as computational biology, bioinformatics, computational cancer immunology, statistics, or a related field.
• Experience analyzing and integrating other high-dimensional molecular datasets, such as multi-omics, bulk RNA-seq, proteomics, flow cytometry, genome-wide genotyping arrays, or clinical data.
• Experience applying machine-learning and AI methods to high-dimensional biological data, such as deep-learning models of cell state, single-cell foundation models, or generative approaches, and judgment about when they offer advantages over established statistical methods.
• Familiarity with computational pathology and multimodal histology-transcriptomics models that predict molecular profiles from H&E images, and interest in applying them alongside spatial transcriptomics.
• Fluency with AI-assisted development tools, such as LLM-based coding assistants and agentic workflows, applied with scientific rigor and validation of outputs.
• Experience working in cloud or high-performance computing environments on large-scale datasets.
• Background in cancer immunology, tumor microenvironment biology, T cell engagers, or drug discovery.

Responsibilities

• Serve as the subject matter expert and hands-on analyst for single-cell and spatial transcriptomics data supporting discovery cancer immunology programs.
• Design and execute end-to-end single-cell and single-nucleus RNA-seq analyses, including cell type and cell state annotation, differential abundance and expression, and cell-cell communication analysis.
• Analyze spatial transcriptomics data from sequencing- and imaging-based platforms, including deconvolution, cell typing, and spatial neighborhood and niche analysis.
• Integrate single-cell and spatial readouts with bulk RNA-seq, high-throughput proteomics, multiplex flow cytometry, genomics, and clinical data to build translational data packages for target concept opportunities.
• Support cancer immunology discovery programs from target identification through candidate selection, including target validation, mechanism of action, and translational hypotheses based on preclinical models and patient-derived samples.
• Partner with biologists and translational teams before data generation to shape experimental design, including platform and panel selection, sample and cohort composition, controls, and statistical power.
• Develop and maintain reproducible, well-documented, reusable analysis workflows and contribute to shared codebases, pipelines, and analytical standards.
• Evaluate, benchmark, and where needed extend emerging computational methods in single-cell and spatial biology, and advocate for methods that provide scientific advantage.
• Communicate findings and recommend follow-up actions in individual discussions, seminars, and team meetings.
• Participate in authoring scientific reports, patents, and publications, and present methods and conclusions to publishable standards.
• Provide scientific mentorship and technical guidance to junior computational scientists and interns, and influence cross-functional matrix teams without formal reporting authority.

Benefits

• Comprehensive benefits, including wellbeing support, retirement and financial protection benefits, and medical, dental, vision, life, and disability insurance offerings, subject to plan terms and eligibility.
• U.S.-based exempt employees are eligible for Flexible Time Off without a set accrual limit, subject to manager approval, and 11 paid company holidays each year.
• Non-exempt employees, RayzeBio employees, and employees located in Puerto Rico receive 160 hours of paid vacation annually for new hires, subject to manager approval, 11 paid company holidays, and 3 optional holidays.
• Depending on eligibility, additional time-off benefits may include paid sick leave, up to two paid volunteer days per year, summer-hours flexibility, and leaves of absence for medical, personal, parental, caregiver, bereavement, or military needs.
• Eligible employees receive an annual Global Shutdown between Christmas Day and New Year's Day.
• May be eligible for additional discretionary incentive cash and stock opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal