Senior Data Scientist Immunotherapy Platform

UT MD Anderson Cancer Center•Houston, TX

22h

About The Position

UT MD Anderson Cancer Center 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 role leads complex analyses of multimodal cancer datasets to uncover mechanisms of tumor–immune interactions and therapeutic response, and independently drives high-impact research projects from analytical design through biological interpretation and publication. The position collaborates with clinicians, immunologists, and researchers, contributes to publications and grant applications, and advances computational approaches in cancer immunotherapy. It offers opportunities to contribute to transformative cancer research, develop advanced computational expertise, and grow through publication and grant involvement in a collaborative, supportive work environment. The role may be responsible for maintaining the security and integrity of critical infrastructure. Routine reviews and screening may be required, and satisfying and maintaining applicable security requirements is a condition of hire and continued employment.

Requirements

Bachelor's degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or a related field.
Five years of experience in scientific software or industry programming with a concentration in scientific computing; three years with a master's degree or one year with a PhD.
Strong programming skills in Python and/or R.

Nice To Haves

PhD in Science, Engineering, or a related field.
Genomics experience.
Experience developing AI models.
Ability to independently lead projects.
Experience with single-cell RNA-seq and/or spatial transcriptomics.
Experience in an academic or healthcare environment.
Experience with multimodal omics data.

Responsibilities

Analyze high-dimensional biomedical datasets, including single-cell RNA-seq, spatial transcriptomics (CosMx, Visium, CODEX), bulk RNA-seq, and clinical datasets.
Characterize the tumor microenvironment, immune cell states, and cell–cell interactions.
Integrate genomic, spatial, proteomic, and clinical datasets.
Develop reproducible and scalable analytical workflows using Python and/or R.
Use public cancer datasets such as TCGA and GEO where appropriate.
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, such as GitHub projects.
Contribute to standardizing analytical approaches across projects.
Generate biologically meaningful insights from complex datasets.
Contribute to manuscripts, with an 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.

Benefits

Employer-paid medical coverage beginning on day one for employees working 30 or more hours per week.
Optional group dental, vision, life, AD&D, and disability insurance.
Accruals for paid time off (PTO) and Extended Illness Bank.
Paid holidays and wellness, childcare, and other leave options.
Tuition Assistance Program after six months of service.
Access to wellness, fitness, and employee resource groups.
Defined-benefit pension through the Teachers Retirement System.
Voluntary retirement plans.
Employer-paid life and reduced salary protection programs.
Educational opportunities and individual and team recognition.