Data Extraction Specialist, Neonatal and Child Health

The Institute for Health Metrics and Evaluation (IHME) is an independent research center at the University of Washington. Its mission is to deliver to the world timely, relevant, and scientifically valid evidence to improve health policy and practice. IHME carries out its mission through a range of projects within different research areas including the Global Burden of Diseases, Injuries, and Risk Factors; Future Health Scenarios; Cost Effectiveness and Efficiency; Resource Tracking; and Impact Evaluations. Our vision is to provide policymakers, donors, and researchers with the highest-quality quantitative evidence base so all people live long lives in full health.

IHME is committed to providing the evidence base necessary to help solve the world’s most important health problems. This requires creativity and innovation, which are cultivated by an inclusive, diverse, and equitable environment that respects and appreciates differences, embraces collaboration, and invites the voices of all IHME team members.

IHME has an outstanding opportunity for a Data Extraction Specialist on our Neonatal and Child Health team. This person will primarily work with an initial focus on blood disorders, anemia, micronutrient deficiencies, hemoglobinopathies, and pregnancy-related health outcomes. The main purpose of this position is to provide highly specialized oversight, guidance, and performance of routine, but complex extraction processes for input data used in modeling at IHME, which will serve research areas including the Global Burden of Diseases, Injuries, and Risk Factors.

This position will work with a dynamic team of researchers and staff at all levels. The Data Extraction Specialist is expected to become knowledgeable in data pertaining to relevant content areas and will consult with researchers as needed to amass data necessary for analysis, presentation, and publication. To create the array of indicators required, this position provides guidance on the extraction of all available relevant quantitative data from surveys, censuses, literature, administrative records, and primary research datasets into central databases. Relevant data include those on mortality, causes of death, epidemiology, and a range of determinants and risk factors, such as education, income, or air pollution.

For more information or to apply, please visit the online job post: https://uwhires.admin.washington.edu/eng/candidates/default.cfm?szCategory=jobprofile&szOrderID=200940&szCandidateID=0&szSearchWords=&szReturnToSearch=1