UX Researcher — AI & Quantitative Specialist

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