Senior Quantitative UX Researcher
Survey design, product analytics, behavioral measurement, experimentation, and product decision support.
UX Research Resume
Senior quantitative UX researcher for high-stakes product decisions.
I help product, design, and data teams turn ambiguous user problems into clear evidence: survey measurement, behavioral analytics, experimentation, segmentation, AI evaluation, and decision-ready mixed-method research.
Role Fit
Where I fit best
I am strongest in roles where research needs to be rigorous enough for statistical scrutiny and practical enough to shape product decisions.
AI / Trust / Measurement Researcher
Evaluation of trust, distrust, reliance, interpretability, human control, and workflow fit in AI-assisted systems.
Mixed Methods UX Researcher
Combining interviews, behavioral data, surveys, prototypes, and workflow evidence into decision-ready synthesis.
Research Scientist-adjacent UXR
HCI background, statistical programming, simulation, measurement design, and applied product research translation.
Evidence of Impact
What I help teams do
Target Roles
Roles where I am easiest to hire well
I am looking for teams that need rigorous research judgment, statistical programming, and product fluency in the same person.
Best match
- Senior / Staff UX Researcher, Quantitative
- AI product research and trust measurement
- Mixed-methods research with strong analytics expectations
Team context
- Product teams with real behavioral data and messy decisions
- Research teams that need stronger measurement systems
- AI or platform teams evaluating human-facing system behavior
Not the best use of me
- Pure interview-only generalist roles with no quant surface area
- Roles with no path from evidence into product decisions
- Environments that treat research as presentation theater
Case Studies
Business-readable case studies
These are intentionally compact and confidentiality-safe. The goal is to show how I frame product questions, choose methods, and translate research into decisions.
Quantifying distrust in an AI-assisted reasoning system
- Problem
- The team needed a defensible way to evaluate distrust, control, and acceptance, not just whether users found the system useful.
- Method
- Trust-scale design, Likert measurement, ordinal modeling, user-type comparisons, and public-safe synthesis.
- What I did
- Turned distrust from a vague concern into measurable constructs that could guide evaluation and product decisions.
- Decision value
- Helped teams reason about where AI assistance increased confidence, where it triggered suspicion, and what to measure next.
Building a persona architecture tied to product decisions
- Problem
- Static personas were not specific enough to guide roadmap, onboarding, messaging, or measurement decisions.
- Method
- Mixed-method synthesis across interviews, preference evidence, workflow observations, and behavioral segmentation logic.
- What I did
- Designed a layered segmentation system connecting behavioral roles, motivations, constraints, and product implications.
- Decision value
- Moved the work from persona storytelling into an operating model for prioritization and post-launch analysis.
Diagnosing a multi-step product journey with high drop-off
- Problem
- A product flow was losing users early, but the team lacked a shared explanation for the behavioral and experiential causes.
- Method
- Journey framing, behavioral baseline design, survey measurement, scorecards, and product analytics interpretation.
- What I did
- Connected observed drop-off patterns to research questions about trust, clarity, friction, and decision confidence.
- Decision value
- Created a reusable baseline for prioritization, benchmarking, and evaluating whether future changes improved the experience.
Experience
Selected applied research leadership
Senior quantitative UX research and statistical consulting
- Designed research programs connecting product questions to measurable user behavior, trust, friction, and decision quality.
- Built survey and analysis workflows using R, Python, SQL, preference modeling, segmentation, and decision-oriented reporting.
- Produced confidentiality-safe evidence packs, research proposals, simulation notebooks, and stakeholder-ready summaries.
Google X / Wing, Microsoft Research, and AI evaluation work
- Led and supported research around autonomous delivery, AI-assisted reasoning, trust-sensitive workflows, and model-driven decision support.
- Developed measurement approaches for trust, distrust, reliance, interpretability, system acceptance, and human control.
- Translated complex technical behavior into research questions product, design, and engineering teams could act on.
Docker, Cloudera, Workday, RightScale/Flexera, and startup-stage work
- Conducted mixed-method and quantitative research for complex workflows, developer tools, cloud platforms, enterprise software, and adoption problems.
- Built segmentation systems, onboarding research, taxonomy validation, heuristic evaluations, benchmark studies, and journey diagnostics.
- Helped teams choose practical next steps when evidence was incomplete, noisy, or distributed across multiple data sources.
Recruiter Keywords
Methods, tools, and product language
Quantitative UX Research
Mixed Methods Research
Survey Design
Experimentation
A/B Testing
Behavioral Analytics
Product Analytics
Segmentation
MaxDiff
Conjoint
Trust and Safety
AI Evaluation
R
Python
SQL
Public Boundaries
Confidential work, public-safe signal
Some of my strongest AI and product research is confidential client or employer work. On this site, I describe methods, problem classes, and public-safe outcomes without sharing proprietary artifacts or materials without permission.