Data Scientist

The Senior Data Scientist within the Institute for Data Science in Oncology collaborates with internal and external stakeholders to drive innovation, expand funding opportunities, support research infrastructure, and accelerate the adoption of data science solutions that improve cancer outcomes., Research, Innovation & Method Development * Design and develop computational methods for advanced research and development in machine learning, AI, numerical analysis, mathematical modeling, and data processing techniques

• Advance the frontiers of cancer data science through development and support of novel methods aligned with IDSO Focus Areas
• Provide technical and data science method development for image analysis, data analysis, AI, machine learning, software development, and prototype implementation
• Design, analyze, develop, and support formulas, algorithms, and software for complex scientific and mathematical applications

• Lead research and data science projects under the direction of IDSO directors and co-leads Grant Development & Resource Expansion * Develop written proposals to secure funding and expand resources available for cancer data science innovations

• Enable advancement of IDSO priorities through development of grant proposals and funding submissions
• Support all IDSO programs, including focus areas, fellowships, affiliates, and collaborative initiatives, through proposal development and writing

• Support JCCO pilot collaborative projects to advance funding opportunities in partnership with IDSO leadership and affiliates Software, Platforms & Infrastructure * Contribute to the design, development, integration, and support of ecosystem software applications and data science platforms

• Strengthen the UT MD Anderson data science ecosystem through software and platform development initiatives
• Drive integration of focus area technical advances into research and clinical infrastructure

• Develop methods for integrating internal and external computational models into institutional research and clinical environments Collaboration & Translational Research * Foster team-based data science approaches and study designs that advance clinical adoption of data science methodologies

• Support community development, collaboration initiatives, and multidisciplinary partnerships across research programs
• Work with IDSO directors and co-leads to envision new concepts and deliver transformative data science projects

• Design and support translational efforts that accelerate the use of computational tools in healthcare settings Stakeholder Engagement * Collaborate with internal partners and external academic and industry organizations to improve data science infrastructure and platforms

• Communicate technical concepts and project outcomes to diverse stakeholder groups
• Support strategic initiatives that improve ecosystem capabilities and resource availability
• Perform 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.

The ideal candidate has preferred advanced education at the master’s or doctoral level in science, engineering, or a related field, along with experience preparing biological data for AI models, writing successful academic proposals, and supporting translational research studies that advance the adoption of data science, artificial intelligence, machine learning, analytics, or computational tools within healthcare or clinical environments., * Required: Bachelor’s Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.

• Preferred: Master’s Degree Science, Engineering or related field.
• Preferred: PhD Science, Engineering or related field.

WORK EXPERIENCE

• Required: 5 years Experience in scientific software or industry programming with a concentration in scientific computing. or
• Required: 3 years Required experience with Master’s degree. or
• Required: 1 year Required experience with PhD.
• Preferred: Experience preparing data for and creating AI models for biological applications, experience writing successful academic proposals, experience designing & or supporting translational research studies that advanced the adoption of data science, AI/ML, analytics, or computational tools in clinical or healthcare environment. Work Schedule: Hybrid Onsite/Remote Schedule

Minimum $123,000 - Midpoint $154,000 - Maximum $185,000 Work Schedule: Hybrid Onsite/Remote work schedule

Why Us? At UT MD Anderson, this role provides the opportunity to advance transformative cancer data science initiatives, contribute to innovative research programs, develop groundbreaking computational methods, and collaborate with multidisciplinary experts. The position supports professional growth through involvement in high-impact research, grant development, software innovation, and translational science projects while offering flexible hybrid work arrangements and comprehensive benefits.

• 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.