Work with cross-functional Product and UX partners to define research questions, hypotheses, study designs, and success measures tied to adoption, trust, and value. Partner with Product, Data Science, and Data Engineering on behavioral data collection, event taxonomies, experimentation, and continuous insight generation. Analyze user journeys to identify drivers of adoption, friction, hesitation, and abandonment across segments and roles. Design surveys and sampling strategies to measure attitudes, trust, and satisfaction across user populations. Conduct quantitative analysis of survey and behavioral data using regression, significance testing, and multivariate methods to determine which factors drive outcomes. Lead causal and experimental research, including A/B testing, to evaluate how features, nudges, and new experiences affect behavior and business outcomes. Combine behavioral and qualitative data to understand why users behave as they do. Use SQL, R or Python, and BI tools to model data and build dashboards and executive-ready narratives that answer product development questions, with clear findings and recommended next steps. Integrate behavioral insights into product planning, design critiques, experimentation, and post-launch reviews, and partner with designers to turn findings into design recommendations. Develop repeatable, transparent AI-assisted research workflows that balance rigor and velocity and enable partners to make data-backed decisions. Provide thought leadership on AI adoption and behavioral science to senior stakeholders, including recommendations on confidence-to-action and appropriate AI reliance. Mentor teammates on quantitative and behavioral methods, and convert effective methods, templates, and study designs into repeatable tools and standards. 7+ years of experience in behavioral research, behavioral analytics, data science, or a related field, driving measurable business and user outcomes in digital product environments. Demonstrated depth in quantitative and behavioral research at scale, including experimentation and A/B testing, predictive modeling, segmentation and cluster analysis, conjoint modeling, and behavioral telemetry analysis. Experience designing surveys and sampling plans, including questionnaire design, sample size and power calculations, and weighting, and analyzing survey data with regression and multivariate methods. Proficiency in SQL and R or Python, and in statistical methods such as significance testing and modeling. Experience building research reporting frameworks and dashboards within fast-moving, AI-first product organizations. Experience delivering AI-assisted and conversational experiences, including ML or NLP familiarity, conversational analytics, and journey or intent modeling. Experience using AI tools in everyday research practice to improve the speed, scale, and quality of analysis, with a focus on responsible, repeatable workflows. Working competence in qualitative methods, including user interviewing, usability testing, and concept testing. Working knowledge of BI and analytics tools such as PowerBI, along with AI-assisted analytics platforms such as Claude. Demonstrated ability to move between technical rigor and clear stakeholder communication, translating complex behavioral and product data into actionable recommendations. Portfolio or work samples demonstrating problem framing, study design, analysis, and how findings shaped product decisions. Contributes to a collaborative, inclusive team culture through respect, humility, humor, and entrepreneurial spirit, and demonstrates strong curiosity and problem-solving skills. Working understanding of usability heuristics and core design principles, including information hierarchy, chart selection, and progressive disclosure, applied to dashboards, reports, and self-service tools. Academic or professional background in behavioral science, behavioral economics, the social sciences, or a related field. Experience with enterprise SaaS, workforce technology, HR technology, or AI-enabled productivity platforms.