Develop and evaluate approaches and tools for learning healthcare systems, disease screening, population health, and decision science
Requirements
- Familiarity with relational databases, SQL
- Experience manipulating and analyzing complex, large volume, high-dimensionality data from varying sources
- Experience with cloud computing and NoSQL
- Experience with clinical data annotation or communication standards
- Experience in R, python, SAS, or C++
- Familiarity with formal software development methods and/or reproducible scientific workflows (e.g. Jupyter notebooks or Rmarkdown) and version control (e.g. git)
- Experience with statistical or machine learning techniques
- Familiarity with Linux OS operating systems or high-performance computing
Responsibilities
- query, organize, and analyze multi-institutional clinical and biological data
- collaboratively study clinical practices and implement policies and interventions
- contribute to the development of novel computational and informatics methods and tools
- train prediction models that are interpretable, transferable across clinical practices, and equitable
- work closely with faculty and staff of the Departments of Pathology & Laboratory Medicine and Biostatistics, Epidemiology, and Informatics
Other
- Bachelor's Degree and a minimum of 2 years of data or systems management experience or an equivalent combination of education and experience required
- Excellent organizational and time management skills required
- Ability to work independently and apply critical thinking and sound judgment required
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner required
- Strong passion for empirical research and for answering hard questions with data required
