Sr. Data Scientist (Urology)
Core
Lead computational scientist designing, developing, and executing machine learning and simulation models for tumor-ecosystem dynamics and individualized disease trajectories within the Brady Urological Institute.
Role type
Senior IC machine-learning engineer (biomedical simulation)
Builds
ExposoGraph exposome knowledge-graph platform and Cancer Ecology Digital Twin (CEDT) predictive simulation environment
Domain
Biomedical research / Urology / Cancer ecology
Deliverable
production ML models
Required skills
Python, PyTorch, XGBoost, LightGBM, causal inference (double machine learning, ATE/CATE), MLOps (Git, CICD), statistical modeling, data pipeline architecture
Preferred skills
PhD, deep learning (neural networks/ODEs), transformer/diffusion methodologies
Technologies
PyTorch, XGBoost, LightGBM, CausalML, Git
Responsibilities
Design data modeling processes for statistical and simulation models; research state-of-the-art methodologies; lead identification of datasets for modeling; clean, assess quality and bias, explore, analyze, and visualize data; document methods and train others; lead cross-functional teams including developers, analysts, and clinicians
Seniority
Senior, hands-on IC