Data Analyst

Vanderbilt University • Nashville, TN

4d

About The Position

About the Logan Lab The Logan Lab, directed by Dr. Jessica Logan at Vanderbilt University's Peabody College, studies the research methods that scientists use to understand how children learn over time, with a particular focus on the academic skills of children with or at risk for learning disabilities. The lab is also committed to advancing data management, data sharing, and data quality practices across education and developmental science research. Our work is supported by federal funding, including grants from the National Institutes of Health, and spans multiple active projects. This is an opportunity to join a collaborative, intellectually rigorous team and contribute meaningfully to research that has real-world implications for children's learning and development. Position Overview The Data Analyst will play a central role in supporting the empirical work of the Logan Lab across multiple federally funded research projects. This position is well-suited for a quantitatively skilled researcher who thrives on working with complex datasets, values methodological rigor, and wants to contribute to publishable scientific work. The analyst will work closely with Dr. Logan and other lab members on all phases of the research process, from data preparation to dissemination.

Requirements

• Bachelor's degree in quantitative methods, statistics, psychology, education, data science, or a closely related field
• Strong quantitative skills and demonstrated experience with statistical analysis
• Proficiency in at least one statistical computing environment (R strongly preferred; Python, Stata, or SAS also considered)
• Experience with data cleaning and management of real-world, messy datasets
• Excellent written communication skills, including the ability to write clearly for scientific audiences
• Ability to work independently, manage multiple project timelines, and meet deadlines
• Strong attention to detail and commitment to reproducible, transparent research practices

Nice To Haves

• Master's degree in quantitative methods, educational measurement, biostatistics, developmental psychology, or a related quantitative field
• Experience with longitudinal data analysis, multilevel modeling, or structural equation modeling
• Background in or knowledge of child development, learning disabilities, or education research
• Experience contributing to peer-reviewed publications or conference presentations

Responsibilities

• Data Management & Quality Clean, organize, and document datasets from multiple concurrent research projects in accordance with best practices for reproducibility and data sharing
• Build and maintain data management systems, codebooks, and standard operating procedures
• Conduct quality assurance checks to ensure data integrity across collection, entry, and storage pipelines
• Support compliance with federal data sharing and open science requirements (e.g., NIH Data Management and Sharing Policy)
• Data Analysis Conduct quantitative analyses including descriptive statistics, regression modeling, longitudinal and growth curve models, and other methods appropriate to grant aims
• Work with large, complex datasets from educational and developmental research contexts
• Select and apply appropriate statistical methods to address research questions related to child development and academic outcomes
• Develop and maintain well-documented, reproducible analysis scripts (e.g., in R or Python)
• Collaborate with the PI and lab members to interpret findings and plan follow-up analyses
• Scholarly Writing & Dissemination Contribute to the writing and revision of peer-reviewed manuscripts for publication in developmental and educational science journals
• Prepare data summaries, tables, and figures suitable for manuscripts, grant reports, and presentations
• Support the preparation of progress reports and other deliverables required by federal funding agencies
• Assist with literature reviews and background sections for manuscripts and grant materials
• Collaboration & Lab Contribution Work collaboratively with postdoctoral researchers, doctoral students, and master's students on shared projects
• Participate in lab meetings, journal clubs, and research discussions
• Assist with grant-related tasks as needed, including supporting new proposals
• Contribute to a positive, inclusive, and productive lab environment

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees