AI Data Scientist Precision Oncology
About The Position
The AI Data Scientist - Precision Oncology develops and applies advanced analytics, machine learning, and artificial intelligence methods to support precision oncology research and AI-enabled clinical outcome optimization. The role works with large-scale clinical, imaging, pathology, molecular, genomic, registry, and outcomes datasets to generate actionable insights, develop predictive models, and evaluate and support implementation of AI technologies across cancer research and healthcare applications. The position collaborates with AI Data Scientists, AI/ML Engineers, clinicians, and informaticians to build high-quality datasets, conduct statistical and predictive analyses, evaluate AI models, and support scalable oncology AI initiatives. The work sits at the intersection of data science, machine learning, biomedical data science, and cancer research, contributing to multimodal AI, foundation-model, and generative AI efforts intended to advance research and patient care. Other related duties may be assigned by appropriate leadership.
Requirements
- Bachelor's degree in Computer Science, Data Science, Statistics, Biostatistics, Mathematics, Bioinformatics, Biomedical Engineering, Computer Engineering, Electrical Engineering, Informatics, or a related quantitative discipline.
- At least two years of experience in data science, machine learning, analytics, biomedical informatics, healthcare data science, or a related field; relevant experience may be obtained through master's degree research.
- Strong programming skills in Python.
- Experience with statistical modeling, machine learning techniques, SQL, data engineering, data visualization, and collaborative software development tools.
Nice To Haves
- Master's degree in a related quantitative discipline.
- Experience with PyTorch, Hugging Face, or similar machine learning frameworks.
- Experience with large language models (LLMs), foundation models, multimodal AI, or generative AI applications.
- Experience working with clinical, oncology, imaging, molecular, genomic, pathology, or healthcare datasets.
- Experience with survival analysis, outcomes research, longitudinal data analysis, and AI model evaluation or validation.
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 structured and unstructured datasets for AI applications.
- Conduct statistical analyses and real-world evidence studies using large-scale healthcare and biomedical datasets.
- Create dashboards, reports, visualizations, and analytical products that support research, clinical, and operational decision-making.
- Translate complex analytical findings into actionable insights for researchers, clinicians, and institutional stakeholders.
- Collaborate with AI Data Scientists, AI/ML Engineers, clinicians, and informaticians on oncology AI programs and translational research efforts.
- Perform other related duties as assigned by appropriate leadership.
Benefits
- Eligible for an annual Team Member Incentive.
- Eligible for an annual Team Member Merit Increase.
- Comprehensive benefits package, including health, financial, and lifestyle coverage.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
