WIL is seeking a Senior Statistician for STEM workforce research to lead survey and statistical work on science, technology, and STEM workforce indicators as principal investigator. 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 • Serve as principal investigator or co-PI on statistical research proposals on science and technology indicators • Design survey, sampling, estimation, and measurement methods • Integrate federal survey microdata and administrative data on R&D, STEM education, and the STEM workforce • Lead data quality, documentation, and disclosure-avoidance practices • Write methods, analysis, and data-management sections • Contribute qualifications and past-performance narrative to WIL proposals when you authorize naming Apply to be considered. Requirements Required • Track record in survey statistics, official statistics, or science and technology indicator research • Experience with large federal survey microdata or administrative data • Proficiency in R, SAS, Stata, or Python • Publications or technical reports demonstrating research leadership • Comfortable as a project-based contract collaborator; remote US Nice to have • PhD preferred (statistics, survey methodology, economics, or related field) • Prior work with or for a federal statistical agency • Small-area estimation or disclosure-avoidance experience