AI Data Scientist Precision Oncology

Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer.

As the only National Cancer Institute-designated Comprehensive Cancer Center based in Florida, Moffitt employs some of the best and brightest minds from around the world. Join a dedicated team of nearly 11,000 who are shaping the future we envision. Moffitt has been recognized as a Best and Brightest Company to Work For in the Nation and is continually named one of the Tampa Bay Times’ Top Workplaces.

Summary The AI Data Scientist - Precision Oncology develops and applies advanced analytics, machine learning, and artificial intelligence methodologies to support precision oncology research and AI-enabled clinical outcome optimization initiatives. This role works with large-scale clinical, imaging, pathology, molecular, genomic, and outcomes datasets to generate actionable insights, develop predictive models, and support the evaluation and implementation of AI technologies across cancer research and healthcare applications.

The AI Data Scientist works at the intersection of data science, machine learning, biomedical data science, and cancer research.

This position collaborates closely with other AI Data Scientists, AI/ML Engineers, clinicians, and informaticians to develop high-quality datasets, conduct statistical and predictive analyses, evaluate AI models, and support institutionally scalable oncology AI initiatives.

Other related duties as assigned by appropriate Leadership.

Join Moffitt Cancer Center's growing AI and Precision Oncology initiatives and help drive the future of cancer discovery and patient care. As an AI Data Scientist, you'll work at the intersection of artificial intelligence, machine learning, biomedical data science, and oncology, leveraging large-scale clinical, genomic, imaging, pathology, and outcomes data to develop innovative solutions that advance cancer research and improve patient outcomes.

About the Lab Our mission is to improve cancer patient outcomes through AI-enabled precision oncology and clinical decision support. We develop and deploy multimodal AI approaches that integrate clinical, imaging, pathology, molecular, genomic, and longitudinal outcomes data to generate actionable insights that support personalized cancer care.

Working at the intersection of clinical care, translational research, and artificial intelligence, our team collaborates directly with oncologists, radiologists, pathologists, surgeons, nurses, and multidisciplinary care teams to develop solutions that address real-world challenges in cancer diagnosis, treatment planning, response assessment, and survivorship. By translating advances in machine learning, real-world evidence, and multimodal AI into clinically meaningful applications, we strive to deliver the right information to the right clinician at the right time, helping improve outcomes and advance the future of precision oncology.

Position Highlights Apply advanced machine learning, predictive analytics, and AI methodologies to support precision oncology research and AI-enabled clinical outcome optimization initiatives.

Collaborate with AI Data Scientists, AI/ML Engineers, clinicians, and informaticians on institution-wide oncology AI programs and translational research efforts.

Work with diverse biomedical datasets, including clinical, molecular, genomic, pathology, imaging, and outcomes data, to generate meaningful insights that impact cancer care and research.

Contribute to cutting-edge initiatives involving machine learning, multimodal AI, foundation models, and generative AI technologies.

The Ideal Candidate Passionate about applying data science, machine learning, and AI to solve complex healthcare and cancer research challenges.

Brings a strong understanding of real-world oncology data, with experience working across clinical and translational cancer datasets and an appreciation for the challenges of developing AI solutions that support clinical decision-making and improve patient outcomes.

Skilled in programming, statistical analysis, predictive modeling, and working with large, complex datasets.

Thrives in a collaborative, multidisciplinary environment and can communicate complex analytical findings to both technical and non-technical audiences.

Curious, innovative, and excited to evaluate emerging AI technologies and methodologies that can transform oncology research and healthcare outcomes.

Responsibilities Develop, evaluate, and benchmark machine learning models for prediction, prognosis, treatment response, survival analysis, and other oncology-focused applications.

Support training, fine-tuning, validation, and performance assessment of machine learning, multimodal AI, foundation-model, and generative AI applications.

Build, curate, and maintain datasets derived from clinical, imaging, pathology, molecular, genomic, registry, and longitudinal outcomes data.

Perform data exploration, quality assessment, feature engineering, and preparation of…