Senior UX Researcher, Quantitative

Accountabilities: Own the research intake process and quantitative research roadmap, translating questions from product, design, go-to-market, and leadership teams into well-defined studies and prioritizing work according to business impact and decision-making needs. Lead pre-launch research using methods such as MaxDiff, conjoint analysis, stimulus testing, matched cohorts, vignettes, and threshold studies to understand which features, benefits, and messages influence user decisions. Establish clear research hypotheses and decision criteria before fieldwork, and improve study instruments through cognitive interviews and other pretesting methods. Develop and adapt validated measurement scales for concepts such as trust, perceived security, and user comprehension, tracking results across products and markets. Build statistically validated and appropriately sized user segments from existing user profiles and research data. Ensure research quality through robust sampling strategies, weighting, translation processes, fraud prevention, and data-quality controls for a global, crypto-native audience. Collaborate with data science teams to connect survey findings with product usage and behavioral data. Design human evaluation frameworks for AI-assisted financial products, including evaluation rubrics, rater reliability measures, and assessments of whether user trust aligns with actual system reliability. Present findings as clear, evidence-based recommendations, communicating effect sizes, confidence levels, uncertainty, and the implications for product and business decisions. Respond to leadership questions with appropriately scoped research, ranging from existing-data analysis and rapid surveys to comprehensive studies. Establish research standards and provide guidance that enables product managers and designers to conduct reliable lightweight surveys and data-driven validation independently. Requirements: At least 7 years of experience in UX research or applied research, including a minimum of 5 years leading quantitative studies independently from study design through analysis and recommendations. Demonstrated experience conducting quantitative research for financial products, such as brokerage, trading, banking, payments, wealth management, or lending. Strong ability to work autonomously, define research priorities, navigate ambiguous questions, and drive projects toward clear decisions with minimal guidance. Advanced knowledge of survey science, including sampling and weighting, questionnaire design, bias mitigation, data-quality screening, and survey programming using Qualtrics or comparable platforms. Practical experience designing and analyzing MaxDiff and/or conjoint studies. Strong applied statistical skills, including regression, power analysis, and experimental and quasi-experimental research design. Proficiency in R or Python for statistical analysis and data visualization. Experience using AI-assisted research workflows, including support for survey development and analysis-code generation or review, with the ability to rigorously validate all AI-generated outputs. A proven record of quantitative research influencing product or business decisions. Excellent communication skills, particularly the ability to explain complex findings and uncertainty clearly to executives and non-research stakeholders. Additional strengths that would be an advantage: Experience with cryptocurrency, onchain products, or tokenized assets. A master’s degree or PhD in a quantitative discipline, such as statistics, survey methodology, behavioral economics, or marketing science. Advanced methodological expertise in areas such as hierarchical Bayes, simulation models, psychometric scale development, segmentation, pricing research, SQL, or multilevel modeling. Experience evaluating AI- or LLM-powered products, including human evaluation frameworks, assessment rubrics, and rater reliability. Experience conducting research across LATAM, APAC, or EMEA markets, including translating and adapting survey instruments. Familiarity with responsible AI-enabled research practices, such as using LLM tools to accelerate instrument development, open-ended response coding, and analysis. Benefits: Competitive compensation, which may include salary, future token rights, and/or equity, with options aligned to individual preferences. Comprehensive medical, dental, and vision coverage. Flexible paid time off and vacation policy. Remote-first working environment with a geographically distributed team. Opportunity to join at an early stage and contribute to the development of the organization's vision, culture, and research and design practices. Opportunity to collaborate with experienced professionals from leading organizations across finance, technology, consulting, and digital assets.