Senior Data Scientist Immunotherapy Platform

UT MD Anderson is seeking a Senior Data Scientist (Computational Biology) to support advanced translational research within the Immunotherapy Platform (IMT) at the James P. Allison Institute. The Senior Data Scientist (Computational Biology) will lead complex analyses of multi-modal cancer datasets, helping to uncover mechanisms of tumor–immune interactions and therapeutic response. This role offers the opportunity to independently drive high-impact research projects from analytical design through biological interpretation and publication.
UT MD Anderson is a leading institution focused on cancer care, research, education, and prevention. The Senior Data Scientist (Computational Biology) will play a central role in accelerating scientific discovery within IMT by collaborating with clinicians, immunologists, and researchers, contributing to publications and grant applications, and advancing computational approaches in cancer immunotherapy.

The ideal candidate will have computational experience. Experience with multi-modal omics data, single-cell and spatial transcriptomics. Experience in academic or healthcare environment.

Why Us?
This role offers the opportunity to contribute directly to transformative cancer immunotherapy research at UT MD Anderson, working alongside leading scientists in a highly collaborative environment. The position supports professional growth through publication, grant involvement, and development of advanced computational expertise, while offering a balanced and supportive work environment.
• Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.
• Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.
• Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.
• Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.

Responsibilities
Data Analysis
• Analyze high-dimensional biomedical datasets including single-cell RNA-seq, spatial transcriptomics (CosMx, Visium, CODEX), bulk RNA-seq, and clinical datasets
• Characterize tumor microenvironment, immune cell states, and cell–cell interactions
• Integrate multi-modal datasets including genomic, spatial, proteomic, and clinical data
• Develop reproducible and scalable analytical workflows
• Apply strong programming skills in Python and/or R to data processing and analysis
• Utilize public cancer datasets such as TCGA and GEO where appropriate

Project Development
• Design and execute end-to-end computational analyses aligned with IMT research priorities
• Propose independent analytical strategies and hypotheses
• Collaborate with experimental and clinical teams to refine biological questions
• Develop reusable pipelines and analytical frameworks (e.g., GitHub)
• Contribute to cross-project standardization of analysis approaches

Research
• Generate biologically meaningful insights from complex datasets
• Contribute to manuscripts with expectation of first or co-first authorship
• Support grant development through computational analysis and data interpretation
• Stay current with emerging computational biology methods and apply them to IMT datasets