Northern Arizona University
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
Northern Arizona University, Flagstaff, Arizona, United States, 86004
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
Join to apply for the
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
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Northern Arizona University Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
1 month ago Be among the first 25 applicants Join to apply for the
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
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Northern Arizona University Get AI-powered advice on this job and more exclusive features. This job was posted by https://www.azjobconnection.gov : For more
information, please see: https://www.azjobconnection.gov/jobs/7008975
r
r**Postdoctoral Scholar, Machine Learning Applications to Improve
Housing Systems**
r
r**Location:** Psychology
r**Regular/Temporary:** Regular
r**Job ID:** 608349
r**Full/Part Time:** Full-Time
r
r Workplace Culture
NAU aims to be the nation\'s preeminent engine of opportunity, vehicle
of economic mobility, and driver of social impact by delivering
equitable postsecondary value in Arizona and beyond.
[](https://apptrkr.com/get_redirect.php?id=6161803&targetURL=https://nau.edu/president/strategic-plan/){_cke_saved_href="https://nau.edu/president/strategic-plan/"
isparent="" target="_blank"}
Special Information
This position is an on-site position which requires the incumbent to
complete their work primarily at an NAU site, campus, or facility
with or without accommodation. Opportunities for remote work are
rare.
The initial appointment is for a duration of 15 months (June 2025 to
August 2026) with the possibility of an extension through May 2027.
This position is posted as **Postdoctoral Scholar, Machine Learning
Applications to Improve Housing Systems** which is a working title.
The NAU system title for this position is **Postdoctoral Scholar**.
This position is subject to the availability of grant funding. The
incumbent is not eligible for Classified Staff layoff or Service
Professional recall status.
Job Description
The Arizona Housing Analytics Collaborative (www.azhac.org) is a
multidisciplinary team of faculty, students, and staff from Arizona
State University, Northern Arizona University, and the University of
Arizona, that leverages cutting-edge data analytics and community-based
evaluation methods to provide actionable insights into housing and
homelessness service delivery systems in the State of Arizona. AzHAC
seeks a Postdoctoral Scholar with training in Data Science, Machine
Learning, and related fields to support the development and deployment
of predictive models/machine learning models aimed at evaluating
programs addressing housing insecurity and homelessness. The AzHAC team
has access to large-scale administrative data sources collected by
state, county, and municipal agencies, and maintains a HIPAA-compliant
high-performance computing environment housed at Arizona State
University to support these analyses. The initial appointment is for a
duration of 15 months (June 2025 to August 2026) with the possibility of
an extension through May 2027. The position is funded by a grant from
the Garcia Family Foundation and will be housed in the Department of
Psychological Sciences at Northern Arizona University (NAU), with
additional supervision provided by faculty from the Department of
Mathematics and Statistics at NAU.
Coordination with AzHAC Team personnel and Stakeholders to Report
Findings - 20%
Coordinate with AzHAC team members and Agency/Community stakeholders
to identify specific criterion and predictor feature attributes
Communicate preliminary findings to stakeholders and develop
collaborative relationships to guide model refinement
Create and distribute presentations, technical documentation, and
manuscripts reporting on model features and findings
Screening, Preparation, and Curation of Raw Data Sources - 20%
Engage in hands-on data preparation and supervise AzHAC Data
Engineers and Data Scientists in the preparation of raw data from
multiple administrative and public-use sources
Lead efforts to generate descriptive visualizations of essential
data elements to ensure quality
Formulation, Construction, Evaluation, and Refinement of Models - 60%
Using Stakeholder input, identify candidate models that answer
substanti e system and program evaluation questions
Build, evaluate and interpret Predictive Models/Machine Learning
Models to examine identified questions
Iteratively refine existing models in response to Stakeholder
feedback, model testing and use, and the acquisition of new data
sources
Minimum Qualifications
PhD or equivalent doctorate (completed by June 1, 2025) in Machine
Learning, Data Science, Predictive Analytics, Statistics, Computer
Science, Quantitative Psychology, Sociology, Public Policy, or
related fields.
The candidate must have extensive documented experience applying
machine learning and predictive modeling techniques to real-world
data.
Preferred Qualifications
PhD or equivalent doctorate (completed by June 1, 2025) in Machine
Learning, Data Science, Predictive Analytics, or Statistics.
Prior experience applying ML/PM to data generated by healthcare,
housing, or government services programs.
Prior experience writing technical reports and dissemination
materials appropriate for a general audience.
Knowledge, Skills, & Abilities
**Knowledge**
Knowledge of contemporary methods in data science, including methods for
continuous outcomes (e.g., spline models) and classificati Seniority level
Seniority level Internship Employment type
Employment type Full-time Job function
Job function Research, Analyst, and Information Technology Industries Higher Education Referrals increase your chances of interviewing at Northern Arizona University by 2x Sign in to set job alerts for “Postdoctoral Researcher” roles.
Postdoctoral Scholar - Gurney Lab, Urban Emissions
Postdoctoral Scholar, Quantum Optics/Optomechanics
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr
Join to apply for the
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
role at
Northern Arizona University Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
1 month ago Be among the first 25 applicants Join to apply for the
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
role at
Northern Arizona University Get AI-powered advice on this job and more exclusive features. This job was posted by https://www.azjobconnection.gov : For more
information, please see: https://www.azjobconnection.gov/jobs/7008975
r
r**Postdoctoral Scholar, Machine Learning Applications to Improve
Housing Systems**
r
r**Location:** Psychology
r**Regular/Temporary:** Regular
r**Job ID:** 608349
r**Full/Part Time:** Full-Time
r
r Workplace Culture
NAU aims to be the nation\'s preeminent engine of opportunity, vehicle
of economic mobility, and driver of social impact by delivering
equitable postsecondary value in Arizona and beyond.
[](https://apptrkr.com/get_redirect.php?id=6161803&targetURL=https://nau.edu/president/strategic-plan/){_cke_saved_href="https://nau.edu/president/strategic-plan/"
isparent="" target="_blank"}
Special Information
This position is an on-site position which requires the incumbent to
complete their work primarily at an NAU site, campus, or facility
with or without accommodation. Opportunities for remote work are
rare.
The initial appointment is for a duration of 15 months (June 2025 to
August 2026) with the possibility of an extension through May 2027.
This position is posted as **Postdoctoral Scholar, Machine Learning
Applications to Improve Housing Systems** which is a working title.
The NAU system title for this position is **Postdoctoral Scholar**.
This position is subject to the availability of grant funding. The
incumbent is not eligible for Classified Staff layoff or Service
Professional recall status.
Job Description
The Arizona Housing Analytics Collaborative (www.azhac.org) is a
multidisciplinary team of faculty, students, and staff from Arizona
State University, Northern Arizona University, and the University of
Arizona, that leverages cutting-edge data analytics and community-based
evaluation methods to provide actionable insights into housing and
homelessness service delivery systems in the State of Arizona. AzHAC
seeks a Postdoctoral Scholar with training in Data Science, Machine
Learning, and related fields to support the development and deployment
of predictive models/machine learning models aimed at evaluating
programs addressing housing insecurity and homelessness. The AzHAC team
has access to large-scale administrative data sources collected by
state, county, and municipal agencies, and maintains a HIPAA-compliant
high-performance computing environment housed at Arizona State
University to support these analyses. The initial appointment is for a
duration of 15 months (June 2025 to August 2026) with the possibility of
an extension through May 2027. The position is funded by a grant from
the Garcia Family Foundation and will be housed in the Department of
Psychological Sciences at Northern Arizona University (NAU), with
additional supervision provided by faculty from the Department of
Mathematics and Statistics at NAU.
Coordination with AzHAC Team personnel and Stakeholders to Report
Findings - 20%
Coordinate with AzHAC team members and Agency/Community stakeholders
to identify specific criterion and predictor feature attributes
Communicate preliminary findings to stakeholders and develop
collaborative relationships to guide model refinement
Create and distribute presentations, technical documentation, and
manuscripts reporting on model features and findings
Screening, Preparation, and Curation of Raw Data Sources - 20%
Engage in hands-on data preparation and supervise AzHAC Data
Engineers and Data Scientists in the preparation of raw data from
multiple administrative and public-use sources
Lead efforts to generate descriptive visualizations of essential
data elements to ensure quality
Formulation, Construction, Evaluation, and Refinement of Models - 60%
Using Stakeholder input, identify candidate models that answer
substanti e system and program evaluation questions
Build, evaluate and interpret Predictive Models/Machine Learning
Models to examine identified questions
Iteratively refine existing models in response to Stakeholder
feedback, model testing and use, and the acquisition of new data
sources
Minimum Qualifications
PhD or equivalent doctorate (completed by June 1, 2025) in Machine
Learning, Data Science, Predictive Analytics, Statistics, Computer
Science, Quantitative Psychology, Sociology, Public Policy, or
related fields.
The candidate must have extensive documented experience applying
machine learning and predictive modeling techniques to real-world
data.
Preferred Qualifications
PhD or equivalent doctorate (completed by June 1, 2025) in Machine
Learning, Data Science, Predictive Analytics, or Statistics.
Prior experience applying ML/PM to data generated by healthcare,
housing, or government services programs.
Prior experience writing technical reports and dissemination
materials appropriate for a general audience.
Knowledge, Skills, & Abilities
**Knowledge**
Knowledge of contemporary methods in data science, including methods for
continuous outcomes (e.g., spline models) and classificati Seniority level
Seniority level Internship Employment type
Employment type Full-time Job function
Job function Research, Analyst, and Information Technology Industries Higher Education Referrals increase your chances of interviewing at Northern Arizona University by 2x Sign in to set job alerts for “Postdoctoral Researcher” roles.
Postdoctoral Scholar - Gurney Lab, Urban Emissions
Postdoctoral Scholar, Quantum Optics/Optomechanics
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr