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Publicado hace 4 días

Research & Data Analyst, Age-Friendly Standards (Full-Time or Part-Time)

Presencial, El trabajo se debe realizar en o cerca de Las Vegas, NV
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  • Descripción

    Tipo de contrato:
    A tiempo completo
    Educación:
    Maestría/Máster
    Compensación:
    USD $12 / hora
    Full-time and part-time options are available. Part-time is approximately 20 hours per week; full-time is approximately 40 hours per week. One-year term, with potential for extension based on performance and funding.
    Área de impacto:
    Adultos mayores, Salud y medicina, Investigación y Ciencias Sociales

    Descripción

    About AAEC

    The American Association for Elder Care (AAEC) is a 501(c)(3) nonprofit working to improve the quality and accessibility of elder care in the United States. Our core initiative is the development of an Age-Friendly Classification system - a standards framework that helps older adults, families, and service providers evaluate whether facilities, programs, and travel experiences genuinely meet the needs of an aging population. AAEC operates as a backend enabler for partner organizations rather than as a direct service provider, which means our research output reaches the field through the partners who adopt it.

    The Role

    We are looking for an analyst to support the research behind our Age-Friendly Classification standards. Both full-time and part-time arrangements are available. This is a small organization, so the work is hands-on and the scope is unusually wide: the criteria you help build will be applied by partner organizations in the field.

    Responsibilities

    - Design and execute data collection protocols across facilities, service providers, and partner networks

    - Clean, structure, and analyze quantitative and qualitative datasets; produce summary statistics and visualizations

    - Conduct literature and policy reviews on aging, long-term care, and accessibility standards

    - Support drafting and revision of classification criteria and scoring methodology

    - Prepare research briefs and documentation for internal and partner use

    Qualifications

    - Master's degree completed or in progress in public health, epidemiology, biostatistics, health policy, gerontology, data science, or a related field

    - Proficiency in at least one analytical tool (R, Python, Stata, or SPSS) and strong spreadsheet skills

    - Ability to write clearly for non-technical audiences

    - Demonstrated interest in aging, long-term care, or health equity

    - Preferred: survey design experience; familiarity with CMS or public health datasets; Mandarin proficiency (a meaningful share of the communities we serve)

    What We Offer

    - Direct mentorship from AAEC leadership and substantive ownership of a standards product you can point to

    - Full-time (approximately 40 hours/week) and part-time (approximately 20 hours/week) options, with flexibility around other commitments

    - AAEC is enrolled in E-Verify and can support STEM OPT training plan documentation for qualifying candidates

    - All applicants authorized to work in the United States are encouraged to apply

    About the Compensation

    We want to be straightforward: this position pays $12.00/hour, which reflects the budget of a small nonprofit rather than the market value of the work. We are looking for someone for whom the research experience, the mentorship, and the portfolio are worth that trade. Both full-time and part-time schedules are available.

    How to Apply

    Send a résumé and a brief note (no more than 300 words) describing an analysis you have run and what you concluded, to Info@aaeldercare.org. Applications reviewed on a rolling basis.

    AAEC is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, citizenship status, or any other protected characteristic.

    Ubicación

    Presencial
    Las Vegas, NV, USA

    Cómo aplicar

    Enviar email

    Send a résumé and a brief note of no more than 300 words describing an analysis you have run and what you concluded. Applications are reviewed on a rolling basis.

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