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MoonPay
London - Hybrid
Source: MoonPay careers ยท View original posting
From MoonPay's posting. โWeโ and โourโ refer to the employer.
MoonPay is for builders with something to prove.
This isn't a "work on cool crypto stuff" company. It's a high-standards, high-velocity, high-accountability company building the operating system for value movement. If the internet moves information, we move value: crypto, stablecoins, tokenized assets, and whatever comes next. Four offerings make that real: fund, tokenize, trade, and spend. 30M+ customers and 500+ ecosystem partners run on us. Licensed in the U.S. Regulated across the UK, EU, Canada, and Australia.
AI is the default operating mode here. It's woven into every role, and we expect you to use it daily. It handles the manual work so you can deliver on what actually matters.
You'll thrive here if outcomes excite you more than process, if impact motivates you more than titles, and if you want hard problems, real ownership, and teammates who love winning, building, and doing it together.
The bar is high. The pace is real. We're building for what's next, for humans and agents.
Forbes' America's Best Startup Employers 2026 .
2nd in Crypto Services on Fortune's inaugural Crypto 100
The Sunday Times Best Places to Work two years running
Research has shown that women are less likely than men to apply for this role if they do not have experience in 100% of these areas. Please know that this list is indicative, and that we would still love to hear from you even if you feel that you are only a 75% match. Skills can be learned, diversity cannot.
Case by case
Remote across Europe, with hybrid working encouraged if you're near a Moonbase (around 2 to 3 days per week in the London office).
In this role, you'll help shape MoonPay's product and business decisions through data, combining deep analysis, experimentation, and strong stakeholder partnership to drive real impact.
You'll sit within our centralised Product Data team and work closely with Product and Engineering, owning analytics across the full product lifecycle, from defining problems and success metrics through to launching, measuring, and optimising products at scale.
Your work will directly influence product strategy, customer experience, and business health, helping teams make better, faster decisions through trusted insights and clear narratives. You'll also raise the leverage of the whole team by building reusable, AI-assisted analytics skills that let the wider org self-serve reliable answers.
This is a great opportunity for someone who enjoys turning complex data into clear direction, influencing decisions, and helping shape the future of high-impact financial and crypto products.
Must-have experience and skills
5+ years of hands-on experience as a data analyst or data scientist, preferably in a product-focused role.
Advanced SQL and data visualisation are second nature to you.
Hands-on experience building data models in a modern cloud warehouse and transformation framework (e.g. dbt with BigQuery, Snowflake), with a strong instinct for data quality.
A solid grasp of statistics and probability, including experiment design and interpretation (A/B and quasi-experimental methods such as difference-in-differences).
A working understanding of how a payments or fintech business operates, including fraud, chargebacks, KYC/AML, and payment success rates.
Comfort using AI-assisted and LLM tools to accelerate analysis, and curiosity about building reusable skills that scale your impact.
Exceptional communication and stakeholder skills. You can distill complex findings for any audience up to C-level, and lead projects independently.
Nice-to-have experience
Familiarity with our stack (dbt, BigQuery, Looker, Python) and AI tooling such as Claude Code.
Hands-on financial crime, payments, or fraud analytics experience.
Experience working in start-ups or scale-ups.
Bonus Points
A crypto-native perspective and experience with on-chain and blockchain data (e.g. Dune, Flipside, Chainalysis).
Experience making data self-serve for non-analysts (e.g. semantic layers, metric stores).
Research has shown that women are less likely than men to apply for this role if they do not have experience in 100% of these areas. Please know that this list is indicative, and that we would still love to hear from you even if you feel that you are only a 75% match. Skills can be learned, diversity cannot.
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
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