Northern Arizona University Flagstaff, AZ 86011
Postdoctoral Scholar, Machine Learning Applications to Improve Housing Systems
Location: Psychology
Regular/Temporary: Regular
Job ID: 608349
Full/Part Time: Full-Time
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://nau.edu/president/strategic-plan/
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 substantive 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 classification algorithms (e.g., decision trees, random forests, SVMs, KNN algorithms, etc.), ensemble learning techniques, data reduction and feature selection methods, neural network and deep learning models, and other related tools
• Knowledge of best practices when applying data science tools to support the evaluation of human services programs and the implications for policy and practice
• Knowledge of contemporary coding languages and environments used to deploy and evaluate predictive models (i.e., Python, R).
• Knowledge of general-purpose statistical programming languages (i.e., SAS, Stata) or data visualization tools (e.g., Tableau, Shiny).
Skills
• General organizational and project management skills
• Can develop and maintain a thoroughly documented code base that is based on a transparent and reproducible architecture
• Advanced proficiency in modern data science coding languages and environments
Abilities
• Efficiently identifies analytical project goals, constructs a timeline, and progresses through objectives with minimal oversight
• Communicates frequently and effectively with AzHAC team members and external stakeholders regarding project progress, and is self-directed in the resolution of barriers to progress
• Articulates analytic processes and findings with sufficient detail and accessibility to effectively solicit and accommodate feedback from collaborators and stakeholders with technical and non-technical backgrounds
Background Information
Northern Arizona University requires satisfactory results for the following: a criminal background investigation, an employment history verification and a degree verification (in some cases) prior to employment. You may also be required to complete a fingerprint background check. Additionally, as an employer in the state of Arizona, NAU is required to participate in the federal E-Verify program that assists employers with verifying new employees' right to work in the United States. Finally, each year Northern Arizona University releases an https://in.nau.edu/police-department/annual-security-and-fire-safety-reports/. The report is a result of a federal law known as the Clery Act. The report includes Clery reportable crime statistics for the three most recent completed calendar years and discloses procedures, practices and programs NAU uses to keep students and employees safe including how to report crimes or other emergencies occurring on campus. In addition, the https://in.nau.edu/police-department/annual-security-and-fire-safety-reports/ is combined with the Annual Security Report for the NAU Flagstaff Mountain Campus as this campus has on-campus student housing. This report discloses fire safety policies and procedures related to on-campus student housing and statistics for fires that occurred in those facilities. If you would like a free paper copy of the report, please contact the NAUPD Records Department at (928) 523-8884 or by visiting the department at 525 E. Pine Knoll Drive in Flagstaff.
Salary
• Anticipated salary range is $58,882 - $73,434. Annual salary commensurate with candidate's qualifications and related experience.
FLSA Status
This position is exempt from the overtime provisions of the Fair Labor Standards Act (FLSA) and therefore will not earn overtime or compensatory time for additional time worked.
Benefits
Post-Doctoral Scholars are hired on a contract basis, renewable each fiscal year for a maximum of 4 renewals (5 years) according to terms of the Arizona Board of Regents' http://azregents.asu.edu/rrc/Policy%20Manual/6-310-Conditions%20of%20Postdoctoral%20Scholar%20Service.pdf. NAU offers an excellent benefit package to Post-Doctoral Scholars including generous health, dental and vision insurance; 10 days of vacation and 10 holidays per year; and tuition reduction for employees and qualified family members. New employees are eligible for benefits on the first day of the pay period following their enrollment, after their employment date. Employees will have 31 days from their start date to enroll in benefits. Participation in NAU retirement plans is not available to Post-Doctoral Scholars. More information on benefits at NAU is available at the NAU https://in.nau.edu/human-resources/benefits/.
Learning and Development
Your career at Northern Arizona University includes the opportunity for professional development. https://in.nau.edu/human-resources/orientation/ includes courses to be completed within the first 30 days.
Immigration Suppt/Sponsorship
NAU will not provide any U.S. immigration support or sponsorship for this position.
Application Deadline
May 26, 2025 at 11:59 p.m.
How to Apply
To apply for this position, please click on the "Apply" button on this page. You must submit your application by clicking on the "Submit" button by midnight of the application deadline. If you need assistance completing your application there are instructions available on the https://in.nau.edu/human-resources/or in person in the Human Resources Department located in Building 91 on the NAU Campus - on the corner of Beaver and DuPont Streets.
If you are an individual with a disability and need reasonable accommodation to participate in the hiring process, please contact the Disability Resources Office at 928-523-8773, http://DR@nau.edu, or PO Box 5633, Flagstaff AZ 86011.
Equal Employment Opportunity
Equal Opportunity Employer, including Disabled/Protected Veterans. NAU is responsive to the needs of dual career couples.
https://in.nau.edu/Human-Resources/Posters-Required-by-Law/
NAU is an Employer of National Service. AmeriCorps, Peace Corps, and other National Service alumni are encouraged to apply.
To apply, visit https://apptrkr.com/6161804
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