Research Data Analyst - Tennessee Reading Research Center - UTK

University of Tennessee • Knoxville, TN

4d • Onsite

About The Position

The Tennessee Reading Research Center (TRRC) conducts state- and federally funded research on literacy initiatives, instruction, and assessment. The Research Data Analyst leads specialized data management, analysis, and reporting projects that support TRRC research and related policy and program initiatives. The role designs data collection and reporting tools; consults with internal and external stakeholders to define data needs; and prepares, validates, integrates, secures, and archives complex educational datasets from multiple sources.

The analyst independently addresses complex data issues, selects analytic methods consistent with research standards, and performs advanced statistical analyses involving randomized controlled trials, quasi-experimental studies, and correlational designs. Methods may include propensity score weighting, growth curve modeling, hierarchical linear modeling, regression discontinuity, structural equation modeling, and meta-analysis. The role develops reproducible code, data-quality procedures, reports, queries, tables, and visualizations; presents findings to stakeholders; and produces data products that inform research, data-collection practices, policy decisions, and program initiatives.

The position supports TRRC documentation and open-science practices, maintains records of data and analysis processes, and mentors student workers. It is based onsite in Knoxville, Tennessee. The anticipated hiring range is $70,000–$75,000. Applicants must be legally authorized to work in the United States on a full-time basis without requiring current or future employment-based visa sponsorship.

Requirements

• Master's degree in statistics, educational measurement, biostatistics, or a related field.
• At least 2 years of progressively responsible experience conducting complex statistical analysis with multilevel data.
• Applicable experience with computer languages; examples listed include R, Java, Python, C, C++, Rust, Ruby, SQL, and Haskell.
• Skills in statistical analysis of multilevel data used in social science, education, or health research.
• Skill using R statistical software.
• Skills in SQL programming and importing, exporting, and integrating files and data from multiple programs and sources.
• Ability to work with large, complex, multivariate datasets; check data accuracy and completeness; and troubleshoot and resolve data-quality issues.
• Ability to learn new statistical methods, software, and programming approaches and continually acquire new competencies.
• Knowledge of standards and best practices for documenting code, data transformations, analytic decisions, and codebooks.
• Skill in creating clear, accurate tables, graphs, visualizations, and other data representations.
• Knowledge and proficiency in Microsoft Office applications, including Excel.
• Excellent written, numerical, and graphical communication skills.
• Ability to work quickly and accurately with strong attention to detail.
• Ability to manage multiple assignments, prioritize tasks, solve problems, meet deadlines, and follow through with minimal direction, often under pressure.
• Ability to communicate technical concepts, data issues, analytic methods, and results effectively to end users, research partners, management, and other stakeholders verbally and in writing.
• Must be legally authorized to work in the United States on a full-time basis without current or future need for employment-based visa sponsorship.

Nice To Haves

• Certificate in applied statistical analysis.
• Experience working with statewide longitudinal data systems.
• Advanced knowledge of R packages.
• Demonstrated ability to manage multiple short- and long-term projects, complete work independently with accuracy, thoroughness, and creativity, and meet deadlines under pressure.
• Experience testing applications that enhance data collection and use.
• Advanced verbal communication and writing abilities for disseminating technical results.
• Knowledge of programming languages such as Python, C++, and JavaScript.
• Knowledge of experimental and quasi-experimental research designs.
• Knowledge of Bayesian statistics.
• Knowledge of statistical analyses for multilevel data.
• Knowledge of qualitative and quantitative research, analysis, and statistical methods.
• Knowledge of preK–12 education data.

Responsibilities

• Lead projects involving research data quality, preparation, collection, and reporting.
• Consult with research teams, external partners, and other stakeholders to clarify data needs and develop data-collection and reporting tools, applications, queries, and processes.
• Write documented, efficient, and robust code to import, merge, clean, standardize, link, de-identify, and archive complex datasets from multiple sources.
• Validate dataset integrity and conduct quality-control checks; identify, investigate, troubleshoot, and resolve data errors, inconsistencies, missing data, and preparation issues.
• Collaborate with the Data Engineer, external research partners, and internal research team on data-validity checks, quality-control procedures, data-management practices, and safeguards for personally identifiable information.
• Determine analytic objectives and select appropriate statistical methods, techniques, and evaluation criteria consistent with research policies and standards.
• Participate with the TRRC Director and lead Statistician in selecting methods and analytic approaches appropriate to research questions, study design, available data, and context.
• Investigate and resolve complex analysis issues involving data structure, model specification, assumptions, missing data, and interpretation.
• Conduct advanced analyses, including methods such as propensity score weighting, growth curve modeling, hierarchical linear modeling, regression discontinuity, structural equation modeling, and meta-analysis, as appropriate for study designs.
• Execute analyses using annotated, documented, and version-controlled scripts to ensure reproducibility.
• Develop and deliver reports, tables, graphs, dashboards, and other visualizations for internal and external audiences.
• Present findings, analytic results, and recommendations in clear, accessible formats.
• Create data products that inform research priorities, program initiatives, data-collection practices, and policy decisions.
• Consult with stakeholders about reporting needs, develop ad hoc queries, and provide accurate and timely reports.
• Maintain complete and timely records of data collection, preparation, quality control, transformation, analysis, and reporting processes.
• Create and maintain codebooks, data definitions, data-quality test catalogs, query catalogs, procedural guides, and records of data sources and routine analyses.
• Establish documentation standards that support transparency, reproducibility, continuity, and appropriate data governance.
• Mentor student workers and guide them in data preparation, documentation, quality control, reproducible analysis, and communication of findings.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level