Description

The Institute for Families in Society (IFS) at the University of South Carolina is seeking a Research Associate/Maternal and Child Health (MCH) Health Care Data Analyst. This role is a crucial component of the IFS’s extensive MCH research portfolio. The ideal candidate should possess a strong understanding of the key drivers of maternal and infant health, including inequities and health outcomes. Proficiency in SAS is essential, as the role involves working with large data sets. The candidate should be passionate about making a meaningful impact and thrive in an environment that fosters collaboration and innovation. The IFS MCH portfolio plays a pivotal role in significant efforts to improve maternal and infant health in South Carolina. The state is renowned for its commitment to innovation and collaborative work with various stakeholders, including Medicaid, Public Health, hospitals, and health care delivery systems. Additionally, the IFS collaborates with community-based non-profits and digital health care innovators to address these critical issues. For more information about the IFS’s impact, please visit their websites at https://www.schealthviz.sc.edu/maternal-and-child-health and https://empower-palmetto.sc.edu/.   

 Apply at: https://uscjobs.sc.edu/postings/208796

Requirements

Preferred Qualifications
Experience/training in health services research.
At least 4 years of experience with the analysis of claims/encounter data.
Strongly prefer an understanding of Medicaid, Medicare, and/or private healthcare claims data systems.
Understanding of and/or experience with analysis of electronic health record data, including data elements used in MCH contexts.
Strong proficiency in SAS, SQL, R, and Python.
Knowledge/Skills/Abilities
Strong analytical thinking and attention to detail.
Experience with large relational database administration.
Demonstrated experience in data management and analysis with administrative data, including health or behavioral healthcare claims such as Medicaid, Medicare, private insurance data, or state agency and national datasets; experience with relevant MCH populations preferred.
Proficiency in SAS, SQL, and other statistical analytical software programs (e.g., R, Python).
Demonstrated ability to use analytical and visualization tools such as Excel (including advanced data manipulation techniques) and Power BI.
Interest in public health or issues relevant to health services research, MCH, and health program or policy evaluation.
Ability to plan for and work on multiple projects concurrently.
Ability to exercise sound judgment in making decisions and maintain thorough documentation of the decision-making process.
Exemplary communication skills and ability to communicate effectively, both verbally and in writing, complicated processes to diverse audiences.
Strong commitment to rigorous research methods, objectivity, accuracy of findings, and reproducibility of results.