Curious by nature.
Rigorous by training.

From mathematics to applied research.

I earned both my bachelor’s and master’s degrees in Mathematics from East Tennessee State University. My academic background gave me a strong foundation in mathematical reasoning, statistical thinking, and research. My graduate and undergraduate research also introduced me to the satisfaction of working through difficult problems, testing ideas, and communicating results.

Today, I work as a Survey Sampling Statistician at Fors Marsh. My work focuses on designing sampling strategies, developing survey weights, evaluating nonresponse, and supporting the production of reliable survey estimates. It draws on both the theoretical foundations of statistics and the practical realities of large, complex research projects.

Sound methods and efficiency of action

I enjoy the methodological side of statistics: understanding what a problem requires, choosing an appropriate approach, and thinking carefully about the assumptions behind the results. My work includes survey weighting and calibration, variance estimation, nonresponse bias analysis, and the use of predictive models to estimate response propensity.

I also use generative AI tools as part of my problem-solving toolkit. I have experience developing and refining prompts to support programming, explore statistical and mathematical concepts, and improve technical documentation. I treat these tools as collaborative rather than authoritative: their output still needs to be evaluated, tested, and checked against sound methods and evidence.

I also have a strong appreciation for good analytical workflows. Repetitive tasks such as producing diagnostics, building methodology tables, and generating report visualizations can consume time while introducing opportunities for human error. Whenever practical, I look for ways to automate that work so results are more consistent, reproducible, and easier to review.

Research, teaching, and communication.

Alongside my statistical work, I teach mathematics and statistics at the college level. Teaching has reinforced the importance of explaining technical ideas clearly, meeting people where they are, and making complicated concepts approachable without losing their substance.

My academic interests have also included discrete mathematics and combinatorics. I co-authored a published paper on universal cycles (combinatorial objects modeled on n-cycle graphs), reflecting an interest in mathematical questions that extends beyond my day-to-day applied work.

Whether I'm developing a weighting approach, investigating a dataset, writing code to streamline a workflow, or explaining a statistical concept, I value careful reasoning, clear communication, and methods that stand up to scrutiny.

A foundation in mathematics.