Data Scientist - GU Radiation Oncology - Research

Data Scientist

The University of Texas MD Anderson Cancer Center is dedicated to eliminating cancer through exceptional patient care, groundbreaking research, prevention programs, and education. Within the Radiation Oncology Division, the Data Scientist role supports innovative efforts focused on advancing clinical, operational, and scientific initiatives through data-driven solutions and technological innovation.

The Data Scientist will contribute to the development of algorithms, software tools, and artificial intelligence and machine learning solutions that support complex healthcare and research challenges. The Data Scientist works collaboratively with multidisciplinary teams to transform data into actionable insights while supporting the mission of UT MD Anderson. The Data Scientist role offers the opportunity to apply advanced analytical skills in a world-renowned oncology environment.

The ideal candidate will possess a strong foundation in data science, analytics, software development, artificial intelligence, and machine learning, with the ability to support clinical, operational, and scientific projects. Education, experience, and licensure preferences were not provided; therefore, candidates should demonstrate relevant technical expertise, analytical problem-solving capabilities, effective communication skills, and the ability to work collaboratively in multidisciplinary environments.

Salary Range (40-hour work week): Minimum $51.20/hour - Midpoint $63.94/hour - Maximum $76.68/hour

Why Us?
At UT MD Anderson, the Data Scientist plays a critical role in advancing cancer research, patient care, and operational excellence through innovative data analytics, software development, and artificial intelligence solutions. This position provides opportunities to collaborate with leading clinicians, researchers, and technical experts while contributing to meaningful work that supports the institution's mission and promotes professional growth in a dynamic 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 & Problem Solving

• Analyze complex clinical, operational, and scientific problems through data collection, interpretation, and modeling. • Collaborate with multidisciplinary teams to define problem statements, establish success metrics, and develop solution strategies.

Algorithm, Software & Model Development

• Design algorithms to address specialized technical challenges. • Develop software tools that support clinical, operational, and scientific objectives. • Test and maintain algorithms and software solutions to ensure performance and reliability. • Build and develop AI and machine learning models using supervised, unsupervised, deep learning, and generative approaches.

Machine Learning Pipeline Development

• Build end-to-end data science and machine learning pipelines. • Perform data ingestion activities to support analytical workflows. • Execute data preprocessing and feature engineering processes. • Train, evaluate, deploy, and monitor machine learning models.
Stakeholder Support & Communication • Advise stakeholders on technical issues and analytical solutions. • Assist teams in analyzing and resolving complex technical challenges. • Communicate model outputs, insights, and system behavior to technical audiences. • Translate analytical findings and technical concepts for non-technical audiences.

Professional Competencies

• Demonstrate active listening and consideration of differing perspectives. • Communicate ideas clearly and concisely through verbal and written communication. • Maintain current technical and functional knowledge. • Promote a safe working environment and support equipment safety preparedness. • Assist with orientation and adoption of new equipment when applicable.

EDUCATION

• 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: 3 years Scientific software or industry development/analysis experience. or
• Required: 1 year Required experience with Master's degree. or
• Required: With PhD, no experience required.

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.

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.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.

Additional Information

• Requisition ID: 182872
• Employment Status: Full-Time
• Employee Status: Regular
• Work Week: Days
• Minimum Salary: US Dollar (USD) 106,500
• Midpoint Salary: US Dollar (USD) 133,000
• Maximum Salary : US Dollar (USD) 159,500
• FLSA: exempt and not eligible for overtime pay
• Fund Type: Hard
• Work Location: Hybrid Onsite/Remote
• Pivotal Position: Yes
• Referral Bonus Available?: Yes
• Relocation Assistance Available?: Yes

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