Sr. Data Scientist (Urology)
 Johns Hopkins University | |
 United States, Maryland, Baltimore | |
 Jul 19, 2026 | |
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We are seeking a
Sr. Data Scientist. The Sr. Data Scientist will serve as a data science subject matter expert and lead the design, development, and execution of data science initiatives requiring advanced machine learning and production-level code. The Sr. Data Scientist will research and implement state-of-the-art modeling methodologies, pipelines and ML lifecycle architecture to support projects and downstream decision making. The Sr. Data Scientist will lead digital tool development efforts and conduct analytics to support full use of data procured by the Brady Urological Institute. The Sr. Data Scientist will foster collaboration efforts with data visualization specialists, data engineers, data scientists, analysts, researchers, program managers, coaches, and other external collaborators and partners in support of a portfolio of data projects.
In this role, the Sr. Data Scientist will serve as the lead computational scientist for the Cancer Ecology Center within the Brady Urological Institute, owning the design, development, and production engineering of the Center's machine-learning and simulation models. The Sr. Data Scientist will write and maintain the core modeling codebase " including next-generation development of the ExposoGraph exposome knowledge-graph platform and the build-out of the Cancer Ecology Digital Twin (CEDT), a predictive simulation environment for modeling tumor-ecosystem dynamics and individualized disease trajectories. The Sr. Data Scientist will leverage Python skills across four broad domains: classic ML (regression/classification tasks; e.g., XGBoost/LightGBM), deep learning (neural networks/ODEs; e.g., PyTorch), state-of-the-art transformer/diffusion methodologies, and causal inference (double machine learning, ATE/CATE; e.g., CausalML), as well as utilize MLOps practices such as Git versioning and CICD pipelines. These skills will facilitate translating complex, multi-modal biomedical and environmental datasets into validated, reproducible models that inform research and clinical decision-making. The successful candidate will combine deep analytical modeling and machine-learning expertise with strong software-engineering discipline, the ability to architect data and modeling pipelines from the ground up, and a track record of leading technically rigorous projects from concept to production. Experience bridging research and applied environments, fluency in complex, interpretable, and causal machine-learning methods, and the capacity to collaborate across data engineers, visualization specialists, clinicians, and research scientists are essential. Specific Duties & Responsibilities
Minimum Qualifications
Preferred Qualifications
Technical Skills & Expected Level of Proficiency
The core technical skills listed are most essential; additional technical skills may be required based on specific division or department needs. Classified Title: Sr. Data Scientist | |