Principal Scientist – Computational Cancer Immunology

Bristol Myers Squibb

. Serve as the subject matter expert and hands-on analyst for single cell and spatial transcriptomics data supporting discovery cancer immunology programs .

Posted 10/27/2026full-timeUnited StatesLead💰 $166,770 - $202,086 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in single cell and spatial transcriptomics, integrating high-dimensional molecular datasets, and applying advanced computational methods in cancer immunology. Proficient in developing reproducible analysis workflows and effectively communicating findings to diverse audiences.

Highest-signal resume keywords

Single Cell TranscriptomicsSpatial TranscriptomicsR or Python ProgrammingMachine Learning and AI MethodsCloud Computing Environments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Single Cell RNA-seq AnalysisDifferential Abundance AnalysisCell Type AnnotationHigh Throughput ProteomicsExperimental DesignStatistical AnalysisMulti-Omics IntegrationComputational PathologyVersion ControlWorkflow Management

Soft Skills

Strong Communication SkillsMentorship and Technical GuidanceInfluencing Cross-Functional Teams

Tools & Technologies

SeuratBioconductorScanpySquidpyAI-Assisted Development Tools

Industry Keywords

Cancer ImmunologyDrug DiscoveryTumor Microenvironment BiologyT Cell EngagersComputational Biology

Tech Stack

Tools & technologies

CloudPython

About the role

Key responsibilities & impact

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 analyses of single cell and single nucleus RNA-seq data
Perform cell type and cell state annotation, differential abundance and expression, and cell-cell communication analysis
Analyze spatial transcriptomics data across 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
Support cancer immunology discovery programs from target identification through candidate selection
Partner with program teams on target validation, mechanism of action, and translational hypotheses
Shape experimental design, including platform and panel selection, sample and cohort composition, controls, and powering
Develop and maintain reproducible, well-documented, reusable analysis workflows and contribute to shared codebases, pipelines, and analytical standards
Evaluate, benchmark, and extend emerging computational methods in single cell and spatial biology
Communicate findings and recommend follow-up actions in 1:1s, seminars, and team meetings
Participate in scientific reports, patents, and publications, presenting methods and conclusions to publishable standards
Provide scientific mentorship and technical guidance to junior computational scientists and interns
Influence cross-functional matrix teams without formal reporting authority

Requirements

What you’ll need

Bachelor's degree with 8+ years of academic/industry experience, or Master's degree with 6+ years of experience, or PhD with 4+ years of experience in computational biology, bioinformatics, computational cancer immunology, or a related field
Demonstrated depth in single cell transcriptomics, including independently delivering scRNA-seq analyses from raw data through biological interpretation
Hands-on experience with spatial transcriptomics data from one or more commercial platforms
Experience analyzing and integrating high-dimensional molecular datasets, including multi-omics, proteomics, flow cytometry, genome-wide genotyping array, or clinical data
Advanced hands-on knowledge of R or Python and associated single cell/spatial ecosystems such as Seurat, Bioconductor, Scanpy, or squidpy
Reproducible research practices including version control and workflow management
Experience applying machine learning and AI methods to high-dimensional biological data
Familiarity with computational pathology and multimodal histology–transcriptomics models
Fluency with AI-assisted development tools, including LLM-based coding assistants and agentic workflows
Strong statistical foundation, including experimental design and analysis of nested, repeated-measures, or otherwise non-independent data
Experience working in cloud/high performance computing environments on large-scale datasets
Track record driving and advancing research projects/programs with computational approaches
Experience supporting drug discovery programs and understanding target identification, validation, and candidate progression decisions
Ability to influence, align, and deliver within cross-functional matrix teams without formal authority
Strong oral and written communication skills
Background in cancer immunology, tumor microenvironment biology, T cell engagers, or drug discovery preferred

Benefits

Comp & perks

Additional discretionary incentive cash and stock opportunities
Wellbeing support
Retirement and financial protection benefits
Medical, dental, vision, life and disability insurance offerings
Flexible Time Off (FTO) for U.S.-based exempt employees
11 paid company holidays each year
160 hours of paid vacation annually for eligible new hires
3 optional holidays for eligible employees
Paid sick leave, where eligible
Up to two paid volunteer days per year
Summer hours flexibility
Medical, personal, parental, caregiver, bereavement, or military leaves of absence
Annual Global Shutdown between Christmas Day and New Year's Day
Workplace accommodations/adjustments and ongoing disability support