Data Scientist Immunotherapy Platform

Data Infrastructure & Engineering

• Design and implement biomedical data systems for multi-modal datasets including genomic, single-cell, spatial, proteomic, and clinical data
• Develop and maintain an internal data registry and metadata tracking systems
• Design databases and data models using SQL/NoSQL technologies, schema design, and APIs

• Harmonize and standardize data across datasets and platforms Pipeline Development & Systems

• Develop pipelines for data ingestion, transformation, and integration using ETL/ELT processes
• Utilize workflow orchestration tools such as Nextflow and Snakemake
• Apply strong programming skills in Python, with R as a plus
• Leverage HPC and/or cloud-based environments for scalable processing
• Implement version control and reproducible workflows using Git and container technologies

• Enable lightweight data access and integration with visualization tools or internal data portals Project Development

• Design and implement a centralized internal data system for IMT
• Develop and enforce standardized data schemas across modalities
• Enable efficient querying, access, and reuse of datasets
• Collaborate with computational scientists to support analysis and modeling workflows
• Optimize data pipelines to improve scalability and reduce turnaround time
• Establish best practices for data governance, documentation, and reproducibility

• Support development of internal data access interfaces such as portals or dashboards Research Support

• Support integration of multi-modal datasets for downstream analysis
• Enable data structures compatible with AI and machine learning workflows
• Collaborate with research teams to translate analytical needs into scalable systems
• Evaluate and adopt emerging tools and standards in biomedical data infrastructure
• Contribute to publications through development of computational workflows and systems

Other duties as assigned., This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.

Ideal candidate has experience developing AI-ready models and scalable computational data pipelines, with strong ability to collaborate across multidisciplinary teams to support complex research and data infrastructure needs. Experience working in a academic or healthcare environment., Required: Bachelor’s Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Master’s Degree Science, Engineering or related field. PhD Science, Engineering or related field., Required: Five years experience in scientific software or industry programming with a concentration in scientific computing. With Master’s degree, three years experience. With PhD, one year experience.

Preferred: Experience working with biomedical or genomics data in healthcare or academic environment. Experience with AI models. Experience computational pipelines. Experience supporting research or analytical teams.

This role offers the opportunity to build foundational data systems that directly enable cutting-edge cancer immunotherapy research at UT MD Anderson. By contributing to scalable, AI-ready data infrastructure, individuals in this role will have a meaningful impact on accelerating scientific discovery while developing advanced technical expertise in a collaborative and innovation-driven environment that supports professional growth and work-life balance.

• 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., The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.

UT MD Anderson is a leading institution focused on cancer care, research, education, and prevention. UT MD Anderson is dedicated to advancing scientific discovery and translating breakthrough research into impactful therapies for patients worldwide. The Senior Data Scientist (Data Infrastructure & Engineering) plays a critical role within the Immunotherapy Platform (IMT), supporting multi-modal cancer research through the development of scalable and robust data systems. The Senior Data Scientist (Data Infrastructure & Engineering) will lead efforts to integrate diverse biomedical datasets into a unified ecosystem, while the Senior Data Scientist (Data Infrastructure & Engineering) also collaborates closely with researchers and computational teams to enable efficient, AI-ready workflows.