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Principal Evaluation Lead / Senior Evaluation Methodologist 2026P-0338

12+ Months, Full-Time
Boston, MA, Hybrid
Posted 2 months ago

Ascension LLC is seeking a Principal Evaluation Lead / Senior Evaluation Methodologist to serve as the intellectual and methodological lead for a high-visibility federal education evaluation supporting the U.S. Department of Education’s Institute of Education Sciences. This role will lead the design of rigorous evaluation approaches for the next cycle of Regional Educational Laboratories and Comprehensive Centers, including assessment of prior-cycle outcomes, formative and summative evaluation planning, technical reporting, and development of analytic frameworks that can withstand IES review.

This position is ideal for a senior evaluation professional with deep expertise in education program evaluation, research design, mixed-methods evaluation, statistical analysis, extant data strategy, technical report development, and federal research standards. The selected candidate must be capable of translating complex research questions into defensible evaluation methods, guiding analytic strategy, overseeing interpretation of findings, and ensuring that reports are suitable for federal review and potential publication.

The Department seeks a single evaluation of both the REL and Comprehensive Centers programs to understand how the programs operate separately and together, how states experience services, and whether the programs are improving satisfaction and alignment with state needs. The SOO also requires the evaluation to produce more frequent and actionable findings for timely program improvement, not merely end-of-cycle reporting.

Summary of the Contractor Role

The Principal Evaluation Lead / Senior Evaluation Methodologist will provide senior-level leadership across evaluation design, analytic planning, data collection strategy, technical quality assurance, and reporting. The role will be responsible for shaping the methodological approach for Task 2, Task 3 Part 2 formative and summative evaluation, Task 4 technical reports, and Task 7 Part 2 analysis plans and instruments.

The ideal candidate will bring a disciplined, research-forward mindset and the ability to operate in an environment where findings must be actionable, defensible, and useful to federal decision-makers. This role requires someone who can balance technical rigor with practical program improvement needs, guide a multidisciplinary team, and produce work products that meet IES expectations for quality, objectivity, and transparency.

The SOO states that technical reports must clearly articulate research questions, describe evaluation purpose, methods, and findings, and be of the highest technical quality, suitable for review in a top-tier peer-reviewed journal or equivalent. Reports may be published by IES and are expected to undergo multiple rounds of government and peer review.

The role will also support the development of the Part 2 analysis plan and data collection instruments, including an OMB clearance package with instruments, Supporting Statements A and B, outreach materials, and Federal Register notices.

Anticipated Day-to-Day Activities

The selected contractor will be expected to:

  • Lead the overall evaluation design for prior-cycle outcomes assessment and the option-period formative and summative evaluation.
  • Translate IES research questions into rigorous evaluation methods, analytic frameworks, data collection strategies, and defensible study logic.
  • Develop methodological approaches for assessing REL and Comprehensive Center long-term objectives, short-term outcomes, collaboration, service alignment, state priority alignment, and recipient perceptions.
  • Guide the use of extant performance data, including APRs, AERs, stakeholder feedback surveys, administrative data, and other government-provided performance measurement sources.
  • Determine when primary data collection, extant data analysis, or mixed-methods approaches are needed to answer the evaluation questions.
  • Design formative and summative evaluation approaches that support annual or recurring actionable findings for continuous program improvement.
  • Oversee the development of the Part 2 analysis plan, including research questions, data sources, sampling logic, analytic methods, limitations, and reporting strategy.
  • Lead or provide senior review of OMB clearance materials, including instruments, Supporting Statements A and B, outreach materials, burden assumptions, and Federal Register notice content.
  • Develop survey, interview, focus group, or other data collection instruments aligned to IES research questions and federal data collection standards.
  • Review analytic outputs, statistical results, qualitative findings, and mixed-methods syntheses for methodological soundness and interpretive accuracy.
  • Ensure findings are presented objectively, supported by evidence, and appropriate for federal program improvement and policy consideration.
  • Provide senior technical direction to analysts, data specialists, report writers, and subject matter experts.
  • Engage with a Technical Working Group by preparing methodological materials, framing review questions, integrating expert feedback, and documenting resulting changes.
  • Support biweekly client meetings, milestone briefings, technical discussions, and written responses to COR or IES feedback.
  • Prepare technical report sections covering evaluation design, methodology, limitations, analysis, findings, conclusions, and implications.
  • Review draft technical reports for quality, consistency, logic, and readiness for government and peer review.
  • Apply disclosure avoidance, confidentiality, and secure data handling expectations when working with non-public IES data.
  • Coordinate with project leadership to identify risks related to data quality, response rates, analytic feasibility, schedule, and reporting dependencies.
  • Recommend methodological adjustments that maintain rigor while improving timeliness, usability, and cost effectiveness.
  • Document assumptions, limitations, decision rules, and analytic choices in a clear and auditable manner.

Job Features

Job CategoryProject Management, Strategic Advisory
MINIMUM QUALIFICATIONSMaster’s degree in education research, evaluation, public policy, statistics, psychology, sociology, economics, measurement, social science research, or a closely related field. Doctorate strongly preferred for this level of responsibility | Excellent writing, synthesis, analytical reasoning, and oral communication skills | Ability to work independently, manage ambiguity, identify methodological risks, and provide practical recommendations under time and budget constraints.
REQUIRED SKILLSMinimum of 10 years of progressively responsible experience leading program evaluations, applied research studies, or federally sponsored evaluation efforts.
TECHNICAL SKILLSDemonstrated experience designing formative and summative evaluations for education, technical assistance, capacity-building, evidence-use, or public sector programs. | Demonstrated ability to translate research questions into evaluation designs, data collection plans, analytic frameworks, and technical reporting structures. | Strong knowledge of quantitative, qualitative, and mixed-methods evaluation approaches. | Experience using extant administrative data, survey data, performance measurement data, stakeholder feedback data, and program documentation to assess outcomes and implementation. | Experience developing or reviewing technical reports, evaluation reports, peer-reviewed publications, or federal research deliverables. | Experience supporting or leading OMB clearance package development, including instruments and Supporting Statements A and B. | Familiarity with federal evaluation standards, research ethics, data privacy, confidentiality protocols, and secure handling of non-public data. | Demonstrated experience leading senior-level client discussions, technical briefings, methodological reviews, or expert panel discussions.
DESIRED QUALIFICATIONSPhD or EdD in education research, evaluation, statistics, public policy, economics, psychology, sociology, measurement, or related field. | Prior experience supporting IES, NCEE, RELs, Comprehensive Centers, ED technical assistance programs, state education agencies, regional education agencies, or education capacity-building initiatives. | Experience with evidence-use, technical assistance evaluation, capacity-building evaluation, implementation evaluation, or continuous improvement models. | Experience designing evaluations that include both annual actionable findings and end-of-period summative conclusions. | Experience developing evaluation products for both technical and non-technical audiences. | Experience preparing reports that undergo federal review, external peer review, journal-style review, or publication-level quality review. | Familiarity with statistical software such as R, SAS, Stata, SPSS, Python, or equivalent analytic tools. | Familiarity with qualitative analysis tools such as NVivo, MAXQDA, Dedoose, or equivalent tools. | Experience with survey design, cognitive testing, sampling, response-rate improvement strategies, weighting, nonresponse bias analysis, or stakeholder interview protocols. | Experience advising or facilitating Technical Working Groups, expert panels, advisory committees, or methodological review boards. | Strong understanding of Section 508 accessibility expectations for public-facing federal deliverables. | Professional affiliation or active engagement with organizations such as the American Evaluation Association, Society for Research on Educational Effectiveness, American Educational Research Association, or similar professional communities.
SUITABILITY/SECURITY REQUIREMENTSAbility to obtain and maintain any required federal suitability determination or clearance needed to access IES systems or non-public data | Ability to comply with confidentiality, data protection, and records management requirements. | Ability to access and use the IES secure server if required for analysis of non-public IES data or extant administrative data. | Must follow strict data-use restrictions, including prohibitions against using IES data, inputs, or outputs to train, fine-tune, improve, or update machine learning models or AI systems. The SOO specifically requires secure handling of IES data and prohibits using IES data for AI training or model improvement.

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