Senior/Staff Data Analyst

MoonPay is building the infrastructure for moving value across crypto, stablecoins, tokenized assets, and beyond. With 30M+ customers and 500+ ecosystem partners, the company operates under regulation across the US, UK, EU, Canada, and Australia. Recently named Forbes' America's Best Startup Employers 2026 and ranked 2nd in Crypto Services on Fortune's inaugural Crypto 100, MoonPay is a high-standards, high-velocity organization where AI is the default operating mode and outcomes matter more than process.

As a Senior or Staff Data Analyst on the Product Data team in London (hybrid), you'll own analytics across the full product lifecycle and directly shape MoonPay's product and business decisions. You'll work closely with Product and Engineering to turn complex analysis into clear recommendations that influence strategy, customer experience, and business health.

What you'll do

• Partner with product and business teams to run rigorous analysis—root cause investigations, opportunity sizing, funnel diagnostics—and translate findings into prioritized recommendations as priorities shift
• Define and maintain metric definitions and business context so stakeholders understand performance and AI tools can interpret your data correctly (think Transaction Success Rate, Fraud Rate)
• Set up tracking and monitoring for new launches, measuring their impact on KPIs and flagging unexpected movements with root cause analysis
• Design, run, and interpret experiments including A/B tests and quasi-experimental methods like difference-in-differences when randomization isn't possible
• Build and maintain the reporting layer in dbt and BigQuery with automated alerting and anomaly detection
• Model robust, trusted data in the cloud warehouse while safeguarding quality through testing, documentation, and certification
• Create reusable, AI-assisted analytics capabilities that help the broader organization self-serve reliable answers
• Communicate complex findings to both technical and non-technical audiences up to C-level, driving critical business decisions

What you'll bring

• 5+ years hands-on experience as a data analyst or data scientist, ideally in a product-focused role
• Advanced SQL and data visualization skills, with deep familiarity building data models in modern cloud warehouses using tools like dbt with BigQuery or Snowflake
• Strong statistical and probability foundations, including experiment design and interpretation
• Working knowledge of payments and fintech operations: fraud, chargebacks, KYC/AML, payment success rates
• Comfort using AI-assisted and LLM tools like Claude to accelerate work, plus curiosity about building reusable skills that scale impact
• Exceptional communication and stakeholder management—you distill complexity for any audience and lead projects independently

Nice to have

• Experience with dbt, BigQuery, Looker, Python, or Claude Code
• Hands-on financial crime, payments, or fraud analytics experience
• Background in startups or scale-ups
• Crypto-native perspective with on-chain and blockchain data experience (Dune, Flipside, Chainalysis)
• Experience building self-serve data solutions for non-analysts using semantic layers or metric stores

Work pattern is hybrid across Europe with 2-3 days per week in the London office if you're based nearby, with full remote flexibility across Europe supported. Relocation considered on a case-by-case basis.