I am a graduate-trained data analyst with a background in educational research, social data science, and program evaluation. I hold a bachelor’s degree in Psychological Science and a master’s degree in Learning Sciences & Technologies, and I am currently pursuing a Master’s in Social Data Science at Arizona State University.
My work sits at the intersection of data analysis, research design, and applied evaluation. I have experience working with large-scale administrative datasets (e.g., district-level assessment data), survey instruments, and qualitative data sources, using tools such as Python, R, SPSS/JASP, and Tableau to analyze and communicate findings.
Professionally, I have supported research and data initiatives in higher education, nonprofit, and public health contexts. I am particularly interested in roles that involve education data analysis, research & evaluation, or data-informed decision-making within mission-driven organizations. I value clarity, rigor, and ethical data use, and I aim to produce analyses that are both methodologically sound and accessible to non-technical audiences.
My work sits at the intersection of data analysis, research design, and applied evaluation. I have experience working with large-scale administrative datasets (e.g., district-level assessment data), survey instruments, and qualitative data sources, using tools such as Python, R, SPSS/JASP, and Tableau to analyze and communicate findings.
Professionally, I have supported research and data initiatives in higher education, nonprofit, and public health contexts. I am particularly interested in roles that involve education data analysis, research & evaluation, or data-informed decision-making within mission-driven organizations. I value clarity, rigor, and ethical data use, and I aim to produce analyses that are both methodologically sound and accessible to non-technical audiences.
- Education data analysis and assessment
- Research design and program evaluation
- Equity and demographic analysis
- Mixed-methods research
- Data visualization for non-technical audiences
- Computational thinking and technology in education