Education Finance Researcher; Part-Time

AIR seeks a Part‑Time Education Finance Researcher with expertise in PK‑12 education finance and funding policy to join its growing team of national experts. We are particularly interested in candidates with experience analyzing state and local funding systems for special populations—especially students receiving special education services, English learners, and students who pursue career and technical education—as well as school district finance, accounting, and budgeting practices.

The successful candidate will apply state‑of‑the‑field education finance research methods to address policy‑relevant questions related to state‑, district‑, and school‑level funding. While not required, experience conducting economic evaluations of education programs, particularly cost and cost‑effectiveness analyses, is also a preferred qualification.

Engagements are typically project‑based, part‑time, and may vary in duration and hours depending on project needs, ranging from 25‑70%, on average 20 hours per week.

This position has the flexibility to work remotely within the United States (U.S.) or from one of AIR's U.S. office locations. This does not include U.S. territories.

Established in 1946, with headquarters in Arlington, Virginia, AIR is a nonpartisan, not‑for‑profit institution that conducts behavioral and social science research and delivers technical assistance to solve some of the most urgent challenges in the U.S. and around the world. We generate evidence and apply data‑driven solutions that expand opportunities and improve lives for all.

• Develop research designs to evaluate federal, state, and local PK‑12 education funding policies and estimate the cost of an adequate and equitable education, especially for students receiving special education and English learners.
• Manage or lead projects and tasks, assuming greater responsibility for project management over time.
• Analyze extant financial and administrative data collected by education institutions (e.g., K12 school districts, state education agencies, community colleges) using state‑of‑the‑field education finance research and statistical methods.
• Collect data from primary sources that describe the types and amounts of resources education organizations have in place, their needs, and extent to which they employ evidence‑based resource allocation strategies.
• Prepare written materials (e.g., technical reports, policy briefs) that describe study findings in ways that are accessible and impactful to policymakers and other decision makers.
• Present findings to clients, professional associations, and the public.
• Participate in, and where appropriate lead, efforts to prepare research proposals that generate external funding for education finance‑related research.
• Supervise and provide mentorship and support to junior staff by sharing approaches to solving concrete problems and providing feedback on their work.

Education, Knowledge, and

Experience:

• A Ph.D./Ed.D., or master's degree with 4‑7 years of demonstrated experience, in education policy, economics, or related social science field with expertise in the economics of education, education finance, and/or educational policy setting and/or conducting education research.
• Knowledge or experience analyzing primary and administrative data (and particularly fiscal data) applying state‑of‑the‑field education finance research concepts and empirical methods.
• Demonstrated experience collecting and analyzing a wide variety of primary and secondary educational data including fiscal data detailing school and district expenditures.
• Demonstrated ability to communicate effectively, in writing and verbally, with non‑technical audiences.

• Expertise in advanced social and behavioral science statistical methods including the use of regression models and rigorous program evaluation design including longitudinal data analysis.
• Expertise in using AI models to analyze education finance data to inform policy and resource decision making at the state and district levels.
• Proficiency in a commonly used statistical application (e.g., Stata, R, etc.) and open to learning new statistical tools as required…