Position Focus:
The Yale School of Public Health (YSPH) catalyzes health for all through innovative and collaborative science, learning and action. A portfolio of work, led by Chima Ndumele and Jacob Wallace, focuses on how vulnerable populations connect with and access health care resources with a particular focus on the Medicaid program. This portfolio has two components: 1) research on how the organization of the social safety-net and how its’ design influences access to care and health outcomes; and 2) optimizing the delivery of services in State Medicaid programs, including Connecticut.
This group is seeking a Data Scientist. This is an exciting opportunity for a skilled programmer who is motivated by the opportunity to produce rigorous, empirical evidence to improve public policy. The ideal candidate is an expert programmer who is fluent in either R or Python and other programming languages such Stata, has experience with large and complex health care datasets, knowledge of causal inference, and believes in YSPH’s mission. The individual will be responsible for: working with faculty and the Director of Data Science and Analytics to explore, process, and analyze data to solve specific research questions cleaning, merging, and implementing linkages of data across multiple sources and projects to facilitate research across the group building traditional statistical models and machine learning algorithms for a variety of research projects using data science, econometric, and machine learning methods to extract meaning from data and identify causal relationships creating clear and impactful visualizations of research results for papers/reports, website, memos, and presentations targeting academic researchers and policy-makers writing and reviewing code and documenting best practices sharing coding best practices with incoming pre-doctoral research fellows opportunity to contribute to analysis plans, executing on those plans with regular guidance from the Director of Data Science and Analytics opportunity to make substantive contributions to publications.
Qualifications:
- Master’s Degree in computer science, applied/computational mathematics, engineering, biostatistics, statistics, or a quantitative field such as astronomy or geology, economics, health policy, health services research, public policy, or a related field and two years of experience or an equivalent combination of education and experience.
- Demonstrated ability working with large and complex datasets.
- Fluency in multiple programming languages including either R or Python.
- Knowledge of social science or econometric research methods.
- Strong organizational skills, attention to detail, and ability to prioritize and manage multiple assignments simultaneously.
- Strong interpersonal skills, communication skills, and the ability to interact well with faculty, staff, and research partners internally and externally.