Position Summary
We are seeking a highly motivated Education Research Analyst to join our team and play a pivotal role in advancing federal and state agency's understanding of their education data ecosystems. The analyst will work with a range of education research and program data, including Institute of Education Sciences (IES) longitudinal survey data, data associated with IES studies, and Charter Schools Program data. In this position, you will become a trusted expert on the agency's education data sources, structures, and quality challenges, helping to identify key areas for improvement. You will work closely with client subject matter experts to quickly develop a comprehensive understanding of the agency's most critical education data domains and top education data quality concerns.
As an Education Research Analyst, you will be responsible for developing clear and well-structured analytical plans and conducting in-depth analysis of education datasets, with a primary focus on longitudinal survey data, administrative records, research study data, and charter school program and grantee data. Your work will involve cleaning and preparing education data, designing and adapting code to detect data quality issues, identifying trends, and producing outputs that support research and operational use. You will also lead complex statistical analyses to validate findings, highlight risks, and inform strategic decision-making.
About AEM Corporation
AEM is a recognized market leader in helping education clients improve the programs, systems, processes, and data used to advance student learning. AEM is more than a successful company, it is an engaging and empowering organization with a strong culture of meaningfully supporting all staff. We are looking for team members who are ready to engage and become an integral part of our team as we continue to push to impact the field of education in powerful ways.
What you'll do as a Research Analyst (Key Responsibilities)
- Design and execute complex analyses of IES longitudinal survey data, IES study data, Charter Schools Program data, administrative records, and other federal and state education datasets using Microsoft Excel or statistical tools such as Stata, SAS, R, or Python to quantify issues, test hypotheses, and measure impact.
- Diagnose and improve data quality across survey, administrative, program, grantee, school, and student-level datasets by defining and operationalizing validation rules, profiling checks, reconciliation procedures, and remediation workflows.
- Tell the story with data: build clear, consumable tables, visuals, and narratives (e.g., Power BI/Excel) that help stakeholders make quick, confident decisions
- Contribute to the development of reports, presentations, and visualizations that communicate findings clearly to both technical and non-technical audiences.
- Conduct literature reviews, evidence reviews, and national scans using IES studies, What Works Clearinghouse evidence resources, peer-reviewed research, and other authoritative sources to support client research, policy, and program needs.
- Apply appropriate research and evidence standards when reviewing studies, documenting methods, interpreting findings, and developing research products, including familiarity with What Works Clearinghouse standards and procedures, as applicable.
- Collaborate with stakeholders to understand education data requirements, and translate those requirements into actionable analytical strategies
- Design and program surveys and other education data collections using Qualtrics or comparable platforms, including one-time and longitudinal collections, and support the analysis of established longitudinal survey data.
- Analyze Charter Schools Program data, including grantee, subgrantee, school, performance, monitoring, and program implementation data, to identify trends, assess data quality, support reporting, and inform program decisions.
- Review documentation associated with IES studies and longitudinal surveys, including study designs, codebooks, data dictionaries, technical documentation, weighting procedures, derived variables, and restricted-use requirements, as applicable.
- Contribute to team excellence: share knowledge, patterns, templates, and how-to guides; propose automation and standards that increase velocity and reduce error.
Required Qualifications (What You'll Bring to the Role)
- Experience analyzing complex education data, such as longitudinal survey data, administrative records, research study data, or federal education program data.
- Experience interpreting technical documentation for large education datasets, including codebooks, data dictionaries, sampling documentation, variable construction guidance, and data-use requirements.
- Experience working with IES longitudinal surveys, IES study data, Charter Schools Program data, or comparable federal education datasets.
- Ability to obtain a security clearance via a Public Trust background investigation
- Bachelor's degree in mathematics, statistics, data analytics, engineering, or a related field
- 5+ years of professional data analysis experience (or 3+ years with a related advanced degree, such as a Masters in Public Policy or Masters in Education Research)
- Experienced with ingesting, cleaning, linking, and analyzing large datasets
- Advanced Microsoft Excel (Power Query, PivotTables, complex formulas) skills
- Proficiency with Power BI and Power Apps
- Proficiency with at least one of the following tools: Stata, Python, SAS, or R
- Quantitative and qualitative data analysis skills; able to design a data analysis, integrate structured/unstructured sources, and apply appropriate analytic method
- Demonstrated experience turning ambiguous questions into clear analytic plans and delivering insights that stand up to scrutiny
- Data quality definition and analysis skills; hands-on experience defining rules, measuring quality, and leading remediation with program and IT partners
- Excellent communication and collaboration skills; comfortable facilitating working sessions with government SMEs and presenting to both technical/non-technical audiences
Preferred Qualifications
- Background in program evaluation, statistical testing, causal inference, randomized controlled trials, quasi-experimental designs, or other research designs commonly assessed under What Works Clearinghouse evidence standards.
- Exposure to data governance and metadata/lineage tooling (e.g., Microsoft Purview) and to privacy/security controls in government contexts
- Experience with qualitative and quantitative research including design of data collection tools/protocols and analysis of data
- Experience analyzing data from IES or NCES longitudinal studies and surveys, such as longitudinal student, postsecondary, educator, or early childhood studies.
- Knowledge of IES research programs, study documentation, data products, and evidence standards.
- Experience with Charter Schools Program data, charter school performance data, federal grant or grantee data, or state charter school authorizing data.
- What Works Clearinghouse-certified reviewer status, completion of applicable WWC reviewer training, or demonstrated experience applying WWC evidence standards.
- Experience conducting or supporting systematic evidence reviews, program evaluations, impact studies, quasi-experimental studies, or randomized controlled trials.
- Experience working with restricted-use or privacy-sensitive education data and following applicable data security, confidentiality, and disclosure-avoidance requirements.
- Experience using Super Intelligence tools
- Experience working in a Scrum/Agile delivery model
- Relevant certifications (e.g., Microsoft Data Analyst Associate, Azure Enterprise Data Analyst)
How We Work
- Agile-aligned: We collaborate tightly with product owners / project leads and clients, write clear and specific acceptance criteria, and provide non-technical demonstrations to ensure interim and final outputs meet client needs.
- Team-first: We value expertise without ego. You share what you know, listen to other perspectives, check our resources, ask questions, seek help early, and step in when a teammate needs support. The goal is the best team outcome, not individual ownership of the smartest idea.
- Quality-focused: You care about getting the details right. You check your work, welcome peer review, document decisions, and produce work that can withstand technical and client scrutiny.
- Delivery-oriented: Quality and timeliness go together. You organize your work, communicate risks early, and take ownership of meeting commitments. Whenever possible, you create enough runway for team review rather than delivering at the last minute.
- Practical problem solvers: We value rigorous methods, but we also need people who can apply them. You are hands-on and will personally analyze problems, identify possible solutions, and translate decisions into workable approaches that fit the study, data, schedule, and client requirements.
AEM and its affiliates are equal opportunity employers, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status, or any other characteristic protected by law. - AA M/F/Vet/Disability
Federal law requires AEM and its affiliates to verify identity and employment eligibility with information from your Form I-9. The E-Verify system is used.
The California Consumer Privacy Act of 2018 ("CCPA") imposes specific obligations on businesses processing personal information of California residents. Pursuant to the CCPA, AEM and its affiliates are required to provide applicants who are California residents a notice, used at or before the point of collection of such personal information, which identifies the categories of personal information that may be collected and why AEM and its affiliates collect such information. Applicants can find information about AEM's privacy policy and CCPA here.
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AEM Corporation
$70,000-$80,000
Nov 05, 2026