Job ID: 376052
About the Job
The Institute for Social Research and Data Innovation (ISRDI) at the University of Minnesota is seeking a Research Scientist to contribute to research on public housing, homelessness, and health. The position offers the opportunity to work with novel linked administrative, census, tax, and mortality data resources spanning multiple decades and geographic scales.
The Research Scientist will report to Dr. Andrew Fenelon and Dr. Kaitlyn Berry and will support the following projects:
Project #1: This NIA-funded project is led by Dr. Andrew Fenelon, an Associate Professor in the Division of Epidemiology and Community Health and the Associate Director of the Minnesota Population Center. The objective of this project is to identify the long-term effects of early life exposure to public housing in the mid-20th century-a well-funded, well-maintained, high-quality housing program-on life course health and aging. The current project focuses on the US public housing program in 1940 and 1950. The project draws on a long-run multisource linkage that merges early-life housing information with later-life economic, housing, health, and mortality outcomes. The research team identified all residents of public housing in the full count 1940 census and the project proposes to expand this dataset to the full count 1950 census. The project will link these data at the individual level to a) the 2000, 2010 and 2020 Decennial Census, b) the American Community Survey [contact details available in the full listing], c) IRS 1040 tax records [contact details available in the full listing]), d) Census Numident [contact details available in the full listing]), and e) Cause of death from death certificates. The analysis uses an innovative design, comparing individuals in public housing to their counterparts in surrounding neighborhoods and cities, based directly on known admission criteria for public housing during the 1930s and 1940s. The project examines the effects of early-life public housing experience on later life health and mortality outcomes, cause of death, employment and earnings, housing conditions, and neighborhood outcomes. The Research Scientist will provide methodological, analytical, and substantive support for the project by working with restricted data, developing and implementing statistical models, preparing requests for results disclosure, and contributing to peer-reviewed manuscripts.
Project #2: The Research Scientist will also contribute to an NIH-funded study examining mortality among people experiencing homelessness across the United States. This project is led by Dr. Kaitlyn Berry, an Assistant Professor in the Division of Epidemiology and Community Health and faculty member of the Minnesota Population Center. The project aims to generate the first comparable estimates of homeless mortality at the state and Continuum of Care levels and identify community- and policy-level factors associated with variation in mortality rates. Using restricted-access US Census Bureau data linked with Social Security Administration mortality records, the study will estimate mortality rates among people experiencing homelessness nationwide. The project will then apply advanced statistical and multilevel modeling techniques to examine how local factors, including policies, homeless services, environmental factors, and economic conditions, are associated with differences in homeless mortality across places. The Research Scientist will play a key role in the quantitative components of this mixed methods study, including restricted data management, record linkages, mortality estimation, statistical modeling, and dissemination of findings. This work has the potential to inform evidence-based policies and interventions aimed at reducing mortality and improving health outcomes among people experiencing homelessness.
Position Duties and Responsibilities
About the Job
The Institute for Social Research and Data Innovation (ISRDI) at the University of Minnesota is seeking a Research Scientist to contribute to research on public housing, homelessness, and health. The position offers the opportunity to work with novel linked administrative, census, tax, and mortality data resources spanning multiple decades and geographic scales.
The Research Scientist will report to Dr. Andrew Fenelon and Dr. Kaitlyn Berry and will support the following projects:
Project #1: This NIA-funded project is led by Dr. Andrew Fenelon, an Associate Professor in the Division of Epidemiology and Community Health and the Associate Director of the Minnesota Population Center. The objective of this project is to identify the long-term effects of early life exposure to public housing in the mid-20th century-a well-funded, well-maintained, high-quality housing program-on life course health and aging. The current project focuses on the US public housing program in 1940 and 1950. The project draws on a long-run multisource linkage that merges early-life housing information with later-life economic, housing, health, and mortality outcomes. The research team identified all residents of public housing in the full count 1940 census and the project proposes to expand this dataset to the full count 1950 census. The project will link these data at the individual level to a) the 2000, 2010 and 2020 Decennial Census, b) the American Community Survey [contact details available in the full listing], c) IRS 1040 tax records [contact details available in the full listing]), d) Census Numident [contact details available in the full listing]), and e) Cause of death from death certificates. The analysis uses an innovative design, comparing individuals in public housing to their counterparts in surrounding neighborhoods and cities, based directly on known admission criteria for public housing during the 1930s and 1940s. The project examines the effects of early-life public housing experience on later life health and mortality outcomes, cause of death, employment and earnings, housing conditions, and neighborhood outcomes. The Research Scientist will provide methodological, analytical, and substantive support for the project by working with restricted data, developing and implementing statistical models, preparing requests for results disclosure, and contributing to peer-reviewed manuscripts.
Project #2: The Research Scientist will also contribute to an NIH-funded study examining mortality among people experiencing homelessness across the United States. This project is led by Dr. Kaitlyn Berry, an Assistant Professor in the Division of Epidemiology and Community Health and faculty member of the Minnesota Population Center. The project aims to generate the first comparable estimates of homeless mortality at the state and Continuum of Care levels and identify community- and policy-level factors associated with variation in mortality rates. Using restricted-access US Census Bureau data linked with Social Security Administration mortality records, the study will estimate mortality rates among people experiencing homelessness nationwide. The project will then apply advanced statistical and multilevel modeling techniques to examine how local factors, including policies, homeless services, environmental factors, and economic conditions, are associated with differences in homeless mortality across places. The Research Scientist will play a key role in the quantitative components of this mixed methods study, including restricted data management, record linkages, mortality estimation, statistical modeling, and dissemination of findings. This work has the potential to inform evidence-based policies and interventions aimed at reducing mortality and improving health outcomes among people experiencing homelessness.
Position Duties and Responsibilities
20% Data Resource Development - The Research Scientist will contribute to the development and management of complex, public data resources supporting federally funded projects on housing, homelessness, and health. Responsibilities will include acquiring, cleaning, harmonizing, and documenting data from a range of sources; constructing project-specific databases; and developing reproducible data workflows. For the public housing project (Project #1), this will involve obtaining public-use and…
