Employer description & source details
The individual in this role will partner with clinicians, cross-functional teams, and data engineering to design and execute a clinical data science strategy — defining hypotheses grounded in customer needs, identifying appropriate data sources, conducting quantitative analyses, and communicating results that demonstrably impact patient outcomes and business objectives. Unlike a purely clinical or purely technical role, this position demands both deep clinical understanding of the Ion platform and hands-on proficiency in modern data science methods and tools. Design, implement, and validate quantitative analyses in Python or R — applying appropriate statistical, machine learning, and causal inference methods to Ion device logs, clinical studies/registries, insurance claims databases, and EHR/EMR data — to test hypotheses. Partner with cross-functional teams to assist with the design and execution of global clinical and economic evidence strategies, including designing and supporting clinical trials. Create and maintain well-organized, reproducible codebases with clear documentation, version control, and consistent coding standards. 6+ years of experience with Master's degree or 4+ years with PhD in a quantitative, scientific, or engineering field (e.g., biostatistics, epidemiology, data science, computer science, biomedical engineering, public health, or a related discipline). MD with quantitative research experience also accepted. Experience with Python or R for data analysis, statistical modeling, and visualization. Working knowledge of SQL for querying and managing structured datasets. Demonstrated experience with causal inference methods and study design. Experience with causal inference in a healthcare or medical device context. Experience with data visualization t
Extracted skills: python, sql, gcp, machine learning, data analysis, tableau