Quick Overview
Job Description
UX Researcher — AI & Quantitative Specialist || Location – San Jose, CA Hybrid || Employment type - contract
Job Description:
AI-Native Research
Quantitative
Mixed Methods
Foresight (WOW)
About the Role
We are looking for a curious, data-savvy UX Researcher to join our team as a contactor. This is not a traditional research role — it sits at the intersection of AI-augmented research, advanced quantitative analysis, and cross-team capability building.
You will help accelerate our journey toward an AI-Native research practice by bringing hard-won external experience in using AI tools within research workflows, and by embedding behavioural data fluency across the team. You will work alongside researchers, designers, and product managers — influencing how we work, not just what we deliver.
What You'll Do
AI-Augmented Research
- Apply AI tools actively in day-to-day research workflows — synthesis, analysis, screener design, report generation, and more
- Lead and co-create internal initiatives that accelerate the team's AI adoption and maturity
- Share external best practices and bring fresh thinking to how AI can transform research at scale
- Act as an internal champion for AI-native ways of working, coaching peers and running enablement sessions
Quantitative Research & Statistics
- Design, execute, and analyse quantitative studies including large-scale surveys, concept tests, and benchmark studies [MUST HAVE]
- Apply statistical methods confidently: significance testing, regression analysis, factor analysis, conjoint, Max Diff, and more [MUST HAVE]
- Build clear, insight-led outputs from quantitative data that drive product and business decisions [MUST HAVE]
- Partner with data and analytics teams to ensure research findings are grounded in robust methodology
Behavioral & Product Data Analysis
- Extract, interpret, and story tell with behavioral data from platforms such as Power BI, Amplitude, Mix panel, or similar [MUST HAVE]
- Triangulate product usage data with primary research to surface richer, more actionable insights [MUST HAVE]
- Identify patterns in user behavior that inform hypothesis generation and research prioritization
- Collaborate with engineers and researchers to ensure the team has access to the right data sources and behavioral signals
Qualitative Research
- Plan and facilitate user interviews, usability studies, diary studies, and contextual enquiries
- Apply thematic analysis, affinity mapping, and Jobs-to-be-Done frameworks
- Translate qualitative findings into compelling narratives for product, design, and leadership audiences
Cross-Team AI Acceleration
- Lead AI research initiatives end-to-end — from scoping to delivery — while actively partnering with fellow researchers throughout [MUST HAVE]
- Work alongside researchers across the team to co-develop AI-assisted processes, templates, and playbooks that embed into everyday ways of working [MUST HAVE]
- Collaborate with researchers on shared AI projects, bringing structure and momentum while creating space for others to upskill alongside you
- Identify bottlenecks in research operations and propose scalable, AI-enabled solutions developed with the team, not just handed to them
- Contribute to a culture of continuous learning, methodological rigour, and shared ownership of the team's AI maturity
What We're Looking For
Non-Negotiables
- Demonstrable experience using AI tools within a research context — not just awareness, but active application [MUST HAVE]
- Strong quantitative research skills: survey design, statistical analysis, and insight generation [MUST HAVE]
- Hands-on experience pulling and interpreting behavioural data from Power BI, Amplitude, or equivalent platforms [MUST HAVE]
- Solid grounding in mixed-methods research — you can move fluently between qual and quant [MUST HAVE]
- Experience creating or leading AI-related research initiatives, not just participating in them [MUST HAVE]
Strong Assets
- Experience collaborating cross-functionally with Designers, PMs, and Engineers in agile or product-led environments
- Ability to communicate complex data clearly to non-research stakeholders
- Familiarity with research tooling: User Testing, Qualtrics, Airtable, Maze, or similar
- Confidence working independently as a contractor — you manage your own time and know when to escalate
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