Data Scientist AI Computational

About the role

We seek a talented, energetic, and collaborative AI-driven Data Scientist to develop data science tools and predictive algorithms as part of the development of our flagship platform A3D3a: Adaptive, AI-augmented, Drug Discovery and Development. With expertise in Machine Learning and Deep Learning, the Data Scientist will inform our mission to discover novel therapeutic opportunities for cancer patients. Led by Prof. Bissan Al-Lazikani, Director of Therapeutics Data Science, the intelligent and ever‑learning A³D³a platform is part of MD Anderson's Therapeutics Data Science initiative and part of our ambitious Institute for Data Science in Oncology. A³D³a will accelerate the discovery and impact of novel therapies for cancer by enabling novel opportunities for optimized therapies for patients with a focus on rare and hard‑to‑treat cancers through the development of novel machine learning and AI technologies. Central to this vision, the Data Scientist will innovate and deploy Machine Learning and Deep Learning approaches to uncover hidden therapeutic opportunities in integrated patient data and will work closely with biologists, data scientists, and clinicians. The position is hybrid (onsite/remote).

Responsibilities

• Build data science tools and predictive algorithms focusing on state‑of‑the‑art machine learning models
• Develop novel deep learning approaches and utilize Large Language Models and Graph Neural Networks for cancer data
• Maintain knowledge of cutting‑edge machine learning approaches and technologies and implement these where appropriate
• Perform data wrangling and preparation for deep learning analysis
• Perform statistical analysis
• Produce output for scientific publications and co‑author said publications
• Prepare written reports, manuscripts, and grant applications with investigators

Requirements

Education: Required: Bachelor's Degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field. Preferred: Master's Degree in Science, Engineering or related field. PhD in Science, Engineering or related field.

Experience: Required: Three years of scientific software or industry development/analysis experience. With a Master's degree, one year of experience. With a PhD, no experience required. Preferred: Experience in Machine Learning, Large Language Models, AI Agents, and/or Biomedical Research is a plus.

Skills

• Machine Learning (e.g., Naïve Bayes, Random Forests, Support Vector Machines, etc.)
• Deep Learning (e.g., Convolutional Neural Networks, Graph Neural Networks, Autoencoders, etc.)
• LLM (fine‑tuning, multi‑agents)
• Addressing challenges in Machine Learning / Deep Learning, including data bias, imbalance, and model validation approaches
• Machine‑learning platforms (e.g., TensorFlow, sklearn, Keras, etc.)
• Unix, Python, R/Matlab, or other scripting/programming languages
• Excellent working knowledge of statistical methods and tests

Benefits

• Employer‑paid medical coverage starting day one for employees working 30+ hours/week
• 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
• 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

Pay

Minimum Salary: USD 106,500
Midpoint Salary: USD 133,000
Maximum Salary: USD 159,500