moneyboxapp - Senior UX Researcher
Requirements
• Deep experience with both generative and evaluative research methods, comfortable independently initiating, running and communicating research end to end. • Commercially minded. You connect research to business outcomes and can prioritise and frame your work so it clearly ties back to commercial impact, not just user need. • Excellent at socialising research for impact. Skilled at packaging, presenting and landing insights so they cut through and drive action. • A genuine advocate for the customer and for research as a discipline, focused on where your work will have the greatest impact, with clear examples of embedding research into how products get built. • As an AI-first researcher you proactively use AI tools across your workflow (synthesis, coding, survey scripting, rapid analysis) to work faster and scale impact, without compromising rigor or participant privacy, and you keep pace with new tools as they emerge. • A fantastic communicator with strong presentation skills, especially when sharing impactful insights. • A natural relationship-builder with presence across the business. • Experienced leading research within multidisciplinary teams, equally comfortable working autonomously or collaboratively. • Skilled at working with peers to prioritise effectively, with clear rationale behind your decisions. • Thrive in a fast-paced environment, using lightweight processes, creative thinking, AI-augmented workflows and quick iteration to have a big impact • A keen interest and knowledge of the FinTech industry.
Responsibilities
• This role will be responsible for but not limited to the following: • Bring expertise across a variety of research methodologies, both quantitative and qualitative, online and offline, from at least 5 years' experience, including leading projects and deciding how to best design, manage and deliver research. • Help the business solve the right problems in the right way, building understanding of customer needs, and supporting teams to evaluate their solutions against them. • Partner closely with the analytics team so qualitative insights are backed by quantitative data wherever possible. • Design and run large-scale quantitative surveys that go beyond basic rating scales, using solid reasoning to surface actionable insight. • Bring a commercial lens to research, framing and prioritising work in terms of the value and impact it can drive for the business, not just the customer. • Embed AI tools into day-to-day research work (e.g. transcript/data synthesis, coding, survey design, analysis, reporting), knowing where AI adds speed and where human review and rigor are essential and help the wider team build the same habits. • Be a strong advocate for the customer and for research itself, packaging and presenting insights so they land with stakeholders and drive real decisions, not just sit in a report. • Influence, challenge and enable teams to deliver high-quality product experiences.
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