Printable UX Resume

Anil Gypsy Wild

Senior Quantitative UX Researcher | Mixed Methods | AI Evaluation | Survey Measurement

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Profile

Senior quantitative UX researcher and HCI-trained statistical programmer who helps product teams turn ambiguous user problems into measurable evidence. Strengths include survey design, behavioral analytics, segmentation, experimentation, preference measurement, and AI trust/reliance evaluation.

Best-Fit Roles

  • Senior / Staff Quantitative UX Researcher
  • AI Product Researcher / Trust Measurement Researcher
  • Mixed Methods UX Researcher with quant depth
  • Research Scientist-adjacent UXR

Methods

  • Survey design, scale development, benchmarking
  • MaxDiff, conjoint-style studies, ranking tasks
  • Behavioral analytics, funnels, telemetry, cohorts
  • Segmentation, clustering, classification

Selected Experience

Independent consulting and applied research | 2024-2026

Designed research programs connecting product questions to measurable user behavior, trust, friction, and decision quality. Built R/Python/SQL workflows, simulation notebooks, and stakeholder-ready evidence packs.

Google X / Wing, Microsoft Research, and AI evaluation work

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.

Docker, Cloudera, Workday, RightScale/Flexera, and startup-stage work

Conducted mixed-method and quantitative research for complex workflows, developer tools, cloud platforms, enterprise software, onboarding, adoption, taxonomy, and journey diagnosis.

Tools

R, Python, SQL, reproducible notebooks, statistical simulation, research automation, stakeholder-facing research artifacts.

Public Boundaries

Some AI and product research is confidential. Public materials describe methods and problem classes without sharing proprietary artifacts.