The University of Pennsylvania is seeking an Associate Data Scientist to help develop and evaluate approaches and tools for learning healthcare systems, specifically in the area of 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 clinical or biomedical data
- 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)
Responsibilities
- Query, organize, and analyze multi-institutional clinical and biological data
- Collaboratively study clinical practices and implement policies and interventions related to disease screening, population health, and decision science
- Contribute to the development of novel computational and informatics methods and tools, including for training prediction models
- Take a leadership role in the training of machine learning prediction models and/or the development of software for the training and application of prediction models
- Work closely with faculty and staff of the Departments of Pathology & Laboratory Medicine and Biostatistics, Epidemiology, and Informatics
- Develop and evaluate approaches and tools for learning healthcare systems
- Implement policies and interventions related to disease screening, population health, and decision science
Other
- Bachelor's Degree and a minimum of 2 years of data or systems management experience or an equivalent combination of education and experience
- Excellent organizational and time management skills
- Ability to work independently and apply critical thinking and sound judgment
- Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
- A strong passion for empirical research and for answering hard questions with data
