Data Scientist II

Implement cutting-edge statistical and machine learning (ML) algorithms to solve complex biomedical, epidemiologic, and clinical problems. Design and validate inferential and causal models to support hypothesis-driven research. Develop and deploy reproducible models for analyzing large-scale clinical and real-world healthcare datasets. Manage, preprocess, and transform structured and unstructured clinical data adhering to best practices in reproducibility and data integrity. Investigate and conduct advanced data visualization and communication to enable scientific insight generation and stakeholder communication. Generate real-world evidence (RWE) and clinical insights by evaluating model performance, uncertainty, and generalizability. Collaborate effectively with clinicians, key opinion leaders, researchers, data engineers, software developers, business stakeholders, and bioinformaticians to formulate clinical questions into actionable analysis plans and strategies. Support and lead the writing of scientific manuscripts, abstracts, and technical reports.