Economist - Education Policy

WIL is seeking an Economist in education policy to lead causal research on K-12 education policy and student outcomes using large administrative datasets.

About the Workforce Intelligence Lab (WIL)

The Workforce Intelligence Lab (WIL) is an applied workforce research initiative. WIL builds methodology-transparent workforce intelligence, including labor demand signals, occupational and credential pathways, and training-to-employment outcome measures, and works with education, employer, research, and community partners to turn that evidence into grant and sponsored-project collaborations. Learn more: https://wilinstitute.org

Opportunity type: this is a contingent proposal opportunity in WIL's expert collaborator network, not a funded vacancy. It supports a competitive grant application WIL is preparing; no award has been made, and there is no guaranteed work or funding. If an award proceeds and the staffing model calls for it, WIL may offer a project-based contract or consulting engagement. We will ask before naming you or including your resume in any proposal.

What you'll do

• Design causal research (quasi-experimental or experimental) on K-12 education policy questions
• Acquire and analyze large administrative education datasets
• Lead estimation, robustness checks, and interpretation
• Write research design, methods, and dissemination sections of proposals
• Produce publication-quality papers and policy briefs
• Contribute qualifications and past-performance narrative to WIL proposals when you authorize naming

Apply to be considered.

Requirements

Required

• Published or working-paper record using causal-inference methods in education or labor economics
• Experience with large administrative education or labor datasets
• Proficiency in Stata, R, or Python for applied econometrics
• Clear writing for research and policy audiences
• Comfortable as a project-based contract collaborator; remote US

Nice to have

• PhD preferred (economics, public policy, education, or related field)
• Prior foundation- or federally funded education research
• State education data-sharing agreement experience