- Own research intake and the quantitative research roadmap across product, design, go-to-market, and leadership.
- Turn ambiguous research requests into answerable questions and prioritize studies based on how much they reduce risk.
- Use MaxDiff and conjoint to assess which features, benefits, and messages drive decisions.
- Design pre-launch experiments, set decision rules before fielding, and pretest instruments with cognitive interviews.
- Adapt or develop validated scales for trust, perceived security, and comprehension, and track them across products and markets.
- Create statistically validated, sized user segments.
- Design sampling, translation, and fraud controls for a global, crypto-native audience.
- Partner with data science to link survey data with product data.
- Design human evaluations of AI-assisted finance features, including rubrics and rater reliability.
- Present findings and recommendations to leadership, including effect sizes, confidence, and what could change the recommendation.
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