What the work actually looks like.
Three engagements that show how I structure mixed-methods research at enterprise scale. Each is abstracted to protect client confidentiality — specific product names and internal tools are genericized, while the methodology, scale signals, and outcomes are intact. Most of this work was done inside AWS Fintech R&D between October 2022 and February 2026.
For decision-makers evaluating fit: each case study is structured as Context · Method · Insight · Impact · Reflection. The Reflection sections are the scholar-practitioner voice — what I'd do differently, what generalizes, and what doesn't.
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2022–2026
ResearchOps
Scaling a Research Panel from 800 to 48,000 in Three Years
A panel of 800 internal users grew to 48,000+ across three years inside AWS Fintech R&D. The story isn't the headcount; it's the recruitment-screener architecture, internal compliance approvals, governance structure, and the operations playbook that made the panel sustainable rather than a one-quarter spike. Particularly relevant for organizations building research capacity inside regulated-industry constraints.
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2023–2025
Operations
Building ResearchOps Inside a Hyperscale Enterprise Function
Most research functions never become operational. They stay ad-hoc for years — projects scoped one at a time, findings buried in slide decks. The build inside AWS Fintech reduced time-to-insight by an estimated 60% through standardized intake, prioritization, repository architecture, and stakeholder reporting workflows. The components that scaled, the components that didn't, and the maturity model that came out of it.
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2022–2026
Mixed Methods
Mixed-Methods Research at the Pace of Agile: 22 Product Teams, One Researcher
Single-researcher coverage across 22+ AWS Fintech product teams sounds impossible until you decompose what coverage actually means. Foundational research, evaluative research, longitudinal diary studies, and large-N quantitative work — embedded into delivery cadences without becoming the bottleneck. The 19 reusable templates that institutionalized repeatable discovery, and what those templates couldn't replace.
Have a research problem these patterns might fit?
I'm in selective intake for Q3–Q4 2026 advisory engagements. Initial conversations are 30 minutes and cover scope, fit, and whether I'm the right researcher for the work — not a sales call.