From cemeteries to video games — my research career spans academic anthropology, EdTech product strategy, and UX insights at a major game studio. I bring the same discipline to every domain: translate messy human behavior into decisions that move products forward.
Whether through segmentation, user feedback, or targeted interviews, I love turning tough questions into clear, practical next steps.
I start with the decision to be made, explore quickly to open the space, validate what matters, then synthesize into actions teams can ship.
Define the decision, hypotheses, and success criteria. Inputs: stakeholder interviews, prior data, constraints. Output: decision brief & study plan.
Lightweight discovery — interviews, concept walkthroughs, early patterns — to surface opportunities and refine assumptions.
Quantify what matters: survey design, message/feature testing, A/B or cohort reads. Output: effect sizes & confidence.
Merge qual + quant into usable models: themes, segmentation cuts, personas/JTBD, frameworks and narratives.
Land the decision: memos, slim dashboards, and next-step playbooks; follow-ups to verify impact.
Pick the question first. I'll show the right methods and typical study formats.
Mix survey + secondary sources to estimate market size and identify where to play.
Research Areas
My work spans qual, quant, and everything in between — always anchored to the decision the team actually needs to make.
Market Insights
Segmentation, sizing, and opportunity identification — giving teams a clear picture of who they're serving and where the most defensible growth lives.
Product Feedback
Concept testing, feature prioritization, and prototype validation — bridging user perspective and business constraints to sharpen what gets built.
User Experience
Usability studies, friction mapping, and task analysis — pinpointing where the experience breaks down and what it takes to fix it.
Survey Design
Questionnaire design, sampling strategy, and analysis in Qualtrics and R — building measurement instruments that answer the right question cleanly.
Professional projects highlighting end-to-end research. Sensitive details are redacted.
Active-learning innovation grounded in instructor evidence.
Evaluating the market viability of an AI-driven learning tool.
Repeatable framework for assessing product evidence and quality.
Mixed-methods churn investigation combining telemetry analysis and social listening at a major game studio.
Personal projects exploring analytics & visualization.
Python → SQL → Power BI pipeline on a simulated dataset.
More walkthroughs and tutorials are on the way.
My toolkit spans the full research lifecycle — from survey design and statistical analysis to synthesis and stakeholder storytelling.
Masters thesis analyzing burial records from two historic cemeteries to examine socioeconomic patterns in mortality and burial practice.
Chapter contribution discussing identity and inequality in marginalized communities through an anthropological lens.
Whether you're building a research function, evaluating a new tool, or looking for someone comfortable at the intersection of qual, quant, and stakeholder storytelling — I'd love to talk.
Python → SQL → Power BI demonstration on a simulated dataset.
Built a self-directed end-to-end analytics pipeline — simulated transactions in Python, analyzed in SQL, and visualized in Power BI — to build hands-on fluency with the tools that sit alongside research work.
Main dashboard: revenue, AOV, returns, category performance.
Revenue & returns by month: trend inspection.
Product insights: price–quantity and revenue distribution.
Customer segmentation: lifetime value and persona tiers.