Senior UX Researcher AI

We’re looking for a Senior UX Researcher to join our UX Research Program and Practice team and work at the intersection of user research, data science, and AI-augmented research. This is not a traditional generalist research role. You’ll split your time across four distinct workstreams: developing and evaluating AI-driven research tools, analyzing participant data to strengthen recruitment quality, building a structured, machine-readable research repository, and conducting mixed-methods research (including benchmarking and UX measurement). 

What you will do:

• AI research tooling development

  • Contribute to a shared repository of AI-driven UX research tools that augment and scale the research workflow. 

  • Design evaluation rubrics for AI output quality – assessing AI-generated research artifacts for things like accuracy, tone, bias, and interpretive validity. 

  • Iterate on tools based on measurable performance criteria, balancing automation with methodological rigor. 

  • Integrate research tooling into the software development lifecycle (SDLC)

• Participant database and recruitment strategy 

  • Query and analyze the existing participant database (SQL, R, or Python) to identify sampling biases, demographic gaps, and representation issues. 

  • Develop data-driven recruitment strategies that address identified gaps.

  • Design and validate surveys and screening instruments to qualify participants. 

  • Report findings accurately using statistical methods appropriate to the data types involved. 

• Structured research repository

  • Transform qualitative and quantitative research data into atomic, structured units suitable for cross-system consumption. 

  • Define and maintain the schema and taxonomy that make qualitative findings machine-readable and queryable. 

  • Enable downstream systems (AI tools, dashboards, cross-functional workflows) to leverage research findings without manual retrieval. 

  • Ensure data quality and consistency standards across the repository.

• Mixed-methods research 

  • Conduct research using existing data sources – survey backlogs, customer feedback repositories, support tickets, prior study findings – to surface patterns and generate new insights. 

  • Design and execute UX benchmarking studies using standardized instruments to establish baselines and measure change over time. 

  • Pair qualitative findings with behavioral analytics or benchmark data to triangulate insights and strengthen evidence. 

What you will bring:

• 5+ years conducting mixed-methods UX research (qualitative and quantitative) in an enterprise product development environment.

• Bachelor's degree in a technical or human-centered field (e.g., HCI, Data Science, Information Systems, Computer Science, Psychology) or equivalent practical experience.

• Demonstrated ability to navigate complex, ambiguous projects and adapt methods in response to new information or changing conditions.

• Experience developing, evaluating, and using AI/LLM-based tools in a research context and think carefully about reliability and failure modes. 

• Proficiency querying and analyzing large datasets using SQL, R, or Python.   

• Statistical analysis fluency – ability to select and apply methods appropriate to the data type and report findings with confidence.          

• Survey and screener design with attention to sampling validity; proficient in Qualtrics.    

• Experience building or contributing to research repositories, taxonomies, or knowledge management systems 

• Strong understanding of research ethics, particularly participant privacy, data handling, and bias mitigation      

• Experience with secondary analysis— synthesizing findings across multiple existing studies, surveys, or feedback channels.         

Following is considered a plus:

• Comfort working in code repositories and collaborating with engineering teams (Git, Markdown, CLI tools) 

• Prompt engineering, evaluation frameworks, or AI output quality assessment experience.  

• Experience with frameworks like Jobs to Be Done, mental models, or similar approa