Quantitative Researcher, Core Data UX

• Lead and execute end-to-end quantitative user research studies, including behavioral logs/telemetry analysis, experimental evaluations, and large-scale surveys to address ambiguous and high-impact product questions independently.
• Apply advanced statistical modeling and computational techniques (e.g., multivariate regression, causal inference, longitudinal analysis) to large, complex, and noisy datasets using tools like SQL, Python, or R.
• Advocate and scale AI-native research workflows, leveraging advanced analytics platforms to build automated analytical pipelines, custom agent skills, and self-service evaluation tooling for the team.
• Drive cross-functional strategy and alignment, partnering closely with UX designers, product managers, and engineering leads to proactively identify research opportunities, define problem spaces, and embed quantitative excellence into product roadmaps.
• Define, validate, and track novel user-centered metrics and productivity frameworks, delivering compelling data narratives that directly influence core architecture, feature prioritization, and executive decision-making.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 4 years of experience in product research in an applied research setting, including analyzing log data.
• Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, SQL) and working with AI platforms.

Preferred qualifications:

• Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field.
  
• 3 years of experience working with executive leadership (e.g., Director level and above).
• 2 years of experience conducting UX research on products, managing projects, and working in a large, matrixed organization.
  
• Experience with generative AI concepts, large language model (LLM) evaluation, and agentic workflows.
• Experience in applied statistics, experimental design, regression modeling, and causal inference.

• Bachelor's degree or equivalent practical experience.
  
• 4 years of experience in product research in an applied research setting, including analyzing log data.
• Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, SQL) and working with AI platforms.