Senior UX Researcher, Quantitative

JobgetherFinancial technology

Based in the United StatesFull-TimeSenior

Salary not disclosed

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Job Details

Experience: 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.
Required Skills: PythonR

Have at least 7 years of experience in UX research or applied research.
Have at least 5 years of experience independently leading quantitative studies from study design through analysis and recommendations.
Have conducted quantitative research for financial products such as brokerage, trading, banking, payments, wealth management, or lending.
Demonstrate advanced knowledge of survey science, including sampling, weighting, questionnaire design, bias mitigation, and data-quality screening.
Have experience with survey programming using Qualtrics or comparable platforms.
Have practical experience designing and analyzing MaxDiff and/or conjoint studies.
Have applied statistical skills, including regression, power analysis, and experimental and quasi-experimental research design.
Be proficient in R or Python for statistical analysis and data visualization.
Have experience using AI-assisted research workflows and rigorously validating AI-generated outputs.
Have a record of quantitative research influencing product or business decisions.
Be able to explain complex findings and uncertainty clearly to executives and non-research stakeholders.
Be able to work autonomously, define research priorities, navigate ambiguity, and drive projects toward clear decisions.

Own the research intake process and quantitative research roadmap, prioritizing studies based on 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.
Establish 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 trust, perceived security, and user comprehension.
Build statistically validated user segments from existing profiles and research data.
Ensure research quality through sampling, weighting, translation, fraud prevention, and data-quality controls.
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 rubrics, rater reliability measures, and assessments of user trust against system reliability.
Present evidence-based recommendations, explaining effect sizes, confidence levels, uncertainty, and implications for product and business decisions.
Establish research standards and guide product managers and designers in conducting reliable lightweight surveys and data-driven validation.

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