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ITR

Demographic Data Analyst Job at ITR in Oak Ridge

ITR, Oak Ridge, TN, US

Job Description

Job Description
Overview

The Human Geography Group within a Department of Energy facility is currently seeking qualified applicants for the position of Demographic Data Analyst. In this role you will work with a team of talented researchers, engineers, and technologists to support existing population and building occupancy workflows for data development, provide updates to the workflows, and help to drive the next generation of population modeling research in support of critical national security missions through a team-based approach and commitment to excellence.

A successful candidate will work on challenging, multidisciplinary projects that advance our understanding of human processes as they interact with the virtual, natural, and built environment. Solving problems motivated by national security challenges, you will use geospatial analysis, demographic and cultural knowledge to model the relationship between built environment characteristics and human population densities across space and time. You will work within the Human Geography Group and collaborate across the Human Dynamics Section and the Geospatial Science and Human Security Division. You will have the opportunity to support the development of data and models through data driven and statistical methods using open-source demographic, sociocultural and economic data from local to global scales. As a member of the Human Geography Group, you’ll focus on support of daily activities of existing workflows as well as updating and developing new methods and models in discovery of the functional and complex connections between humans and their physical, cultural, and socioeconomic landscapes.

Major Duties and Responsibilities:
  1. Contribute to the systematic development and updating of population models for facility types worldwide, from the local to regional scale.
  2. Leverage a variety of open-source data including censuses and surveys, user generated content, longitudinal or ethnographic data to for building occupancy or population distribution data development.
  3. Use statistical and/or computational methods to enhance the spatial, temporal, and demographic resolution of our modeling and analysis.
  4. Support review, update, and develop new quantitative, qualitative, or mixed methods for updates to statistical building occupancies to accommodate newly discovered open-source data.
  5. Contribute to the development of tools and processes that automate open-source data collection, increasing access and visibility of open-source data and building occupancy and population models to stakeholders and the user community.
  6. Contribute to team publications in journals, participate in conferences, and engage with other scientists, technicians, and analysts in the private sector, academia, and US Government communities.
Basic Requirements
  1. Master’s degree or higher in Geography, Demography, or a related discipline.
  2. Experience in analyzing and interacting with census statistics and microdata, other social/health surveys, and other structured or unstructured open-source datasets.
  3. Experience in geospatial analysis including use of open source and/or commercial geospatial tools such as ArcGIS, QGIS, or PostGIS.
  4. Experience with qualitative and quantitative population research methods with focus on sociocultural and economic spatial and temporal processes in the built environment.
  5. Experience in open-source data mining and collection techniques.
  6. Experience in remote sensing and image interpretation.
  7. Excellent written and oral communication skills.
  8. Capable of working successfully in a team environment.
Preferred Qualifications:
  1. Experience with research or development about different cultures and cultural practices around the world.
  2. Experience with Python, R, and/or other similar languages for statistical analysis.
  3. Experience in analyzing and interacting with social media, digital trace data, or time series data.
  4. Experience with remote sensing and image interpretation including multispectral and hyperspectral data, spectral analysis, and LiDAR.
  5. Fluency in other cultural languages or working knowledge of key word or phrases spoken in another language in support of open-source data collection.
  6. Demonstrated record of research as evidenced by scientific output including peer-reviewed publications.
  7. Experience leading research initiatives with colleagues or team members.