Principal Scientist - Computational Cancer Immunology

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

When you join BMS, you are joining a high-achieving team united by a common mission.

 

The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit.  IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS.   We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company.   We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers.

 

Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma.

We seek a creative and passionate computational biologist with deep expertise in single cell and spatial transcriptomics to join the Oncology team within Informatics and Predictive Sciences (IPS). In this role, you will serve as the scientific lead for single cell and spatial analysis across our discovery cancer immunology portfolio, applying cutting edge computational, machine learning, and advanced statistical methods to high-dimensional patient and pre-clinical data. Partnering closely with biologists, translational scientists, and fellow computational biologists, you will generate and evaluate novel therapeutic hypotheses — resolving the cellular composition, states, and spatial organization of the tumor microenvironment to identify and validate new targets. This is a hands-on individual contributor role in which your scientific depth and influence across matrix teams will directly impact the discovery and development of novel therapies for cancer patients.

Responsibilities

Responsibilities will include, but are not limited to, the following:

• 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, including 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 complementary modalities — bulk RNA-seq, high throughput proteomics, multiplex flow cytometry, genomics, and clinical data — to build holistic translational data packages for target concept opportunities.

• Support cancer immunology discovery programs from target identification through candidate selection, partnering with program teams on target validation, mechanism of action, and translational hypotheses generated from pre-clinical models and patient-derived samples.

• Partner with biologists and translational teams upstream of data generation to shape experimental design, including platform and panel selection, sample and cohort composition, controls, and powering.

• Develop and maintain reproducible, well-documented, and reusable analysis workflows, contributing to shared codebases, pipelines, and analytical standards that benefit the broader IPS organization.

• Evaluate, benchmark, and where needed extend emerging computational methods in single cell and spatial biology, and advocate for their adoption where they create scientific advantage.

• Communicate findings and recommend follow-up actions in multiple settings (including 1:1, seminars, and team meetings). Participate in authorship of 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.

Qualifications

Basic qualifications:

• 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

Preferred qualifications:

• PhD from a recognized institution in a quantitative field such as computational biology, bioinformatics, computational cancer immunology, statistics, or related.

• Demonstrated depth in single cell transcriptomics, with 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.

• Experience analyzing and integrating other high-dimensional molecular datasets, such as multi-omics (e.g., bulk RNA-seq, proteomics), flow cytometry, genome-wide genotyping array, or clinical data.

• Advanced hands-on knowledge of at least one high-level programming language such as R or Python, with fluency in the associated single cell and spatial ecosystems (e.g., Seurat, Bioconductor, Scanpy, squidpy) and with reproducible research practices including version control and workflow management.

• Experience applying machine learning and AI methods to high-dimensional biological data — for example deep learning models of cell state, single cell foundation models, or generative approaches — together with the judgment to know when they offer advantage over established statistical methods.

• Familiarity with computational pathology approaches 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, to accelerate analysis and software development, applied with appropriate scientific rigor and validation of outputs.

• Strong statistical foundation, including experience with experimental design and with the analysis of nested, repeated-measures, or otherwise non-independent data.

• Experience working in cloud/high performance computing environments on large-scale datasets.

• Track record (such as scientific publications) in driving and advancing research projects/programs with computational approaches.

• Experience supporting drug discovery programs, with an understanding of 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.

• Background in cancer immunology, tumor microenvironment biology, T cell engagers, or drug discovery preferred.

We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.

Brisbane - CA - US: $166,770 - $202,086 Cambridge Crossing: $166,770 - $202,086

The starting pay range(s) listed above is for full-time employees (FTE). You may also be eligible for additional discretionary incentive cash and stock opportunities. We determine starting pay thoughtfully – carefully considering the nature of the role, required skills, work location, schedule and the knowledge and experience you bring. Final compensation is guided by pay equity principles and applicable employment laws. Compensation programs are reviewed on an ongoing basis and may be adjusted over time to reflect evolving market factors, and individual, team or Company performance.

Benefits:

Subject to the terms and conditions of the applicable plans then in effect, you may be eligible to participate in our comprehensive benefit plans – including wellbeing support, retirement and financial protection benefits, and insurance offerings (medical, dental, vision, life and disability).

U.S.-based exempt employees are eligible for Flexible Time Off (FTO), which provides paid time off without a set accrual limit, subject to manager approval, along with 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, employees may also have access to additional time-off benefits, including 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 also enjoy an annual Global Shutdown between Christmas Day and New Year's Day.

U.S.-based job seekers can explore full benefit offerings at https://careers.bms.com/benefits

How We Work

Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.

Supporting People with Disabilities

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

For roles based in Los Angeles County only:  If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/

For roles based in Washington State only: If you live in or expect to work from Washington State if hired for this position, please visit this page for important information about the Washington Fair Chance Act.

Data Protection

We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection.

Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.comwith the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.

R1607771 : Principal Scientist - Computational Cancer Immunology