Staff Growth Data Scientist, Monetization

MoonPay
London
1 month ago
Create job alert

Staff Growth Data Scientist, MonetizationStaff Growth Data Scientist, Monetization

2 weeks ago Be among the first 25 applicants

Hi, we’re MoonPay. We’re here to onboard the world to the decentralized economy.
Why?
Because crypto and blockchain aren’t just technologies—they’re tools for global financial empowerment. They give people control over their money, their digital assets, and their future, unlocking opportunities that traditional systems have kept out of reach.

What We Do
At MoonPay, we’re building the infrastructure that powers this new financial system. We make it easy for anyone, anywhere, to buy, sell, and trade crypto using everyday payment methods like cards, Apple Pay, PayPal, Revolut and Venmo. We provide simple tools to send, receive, and manage stablecoins, so anyone can participate in the crypto economy confidently.

Trusted by nearly 30 million customers and over 500 companies, our secure, enterprise-grade platform is driving mainstream crypto adoption worldwide.

We collaborate with innovative brands and projects to build secure, scalable solutions for a blockchain-powered future. And we’re committed to doing it right—fully licensed in the U.S. and regulated across the UK, EU, Canada, and Australia—because trust and compliance are non-negotiable.

But we’re just getting started. We’ve launched a consumer app that makes crypto accessible, intuitive, and usable for everyone, and it’s growing fast. We’re iterating every day to make it the best it can be.

If you believe financial freedom should be for everyone—if you believe in building a fairer, more open financial system—we want you with us. To build systems that benefit all, we need contributions from all, regardless of background.

Come build the future of payments and the decentralized economy with MoonPay. Let’s make financial freedom and autonomy the new normal.
About The Opportunity ️
We are seeking a highly analytical and strategic Growth Data Scientist to drive pricing and monetization for MoonPay's Products.

As a Growth Data Scientist, you will be responsible for building our dynamic pricing algorithms, designing incentive and reward mechanisms, and developing a comprehensive strategy to optimize volume & revenue generation across the entire suite of MoonPay products and business lines. You will also be responsible for launching AB tests and quasi-experiments, analyzing data to identify opportunities for margin optimization, and developing an analytical infrastructure to track the performance of pricing optimizations. This role requires a deep understanding of marketplace dynamics, experimentation, causal inference, pricing strategies in B2C / B2B2C / B2B environments, and solid technical acumen.

What You Will Do

  • Build pricing algorithms to manage fee configurations on marketplaces dynamically
  • Develop monetization strategies that strike a balance between volume and margin, considering factors such as competitor prices, purchase order size, payment methods, currency pairs, user types, and geographies
  • Conduct market research and competitive analysis to identify trends, opportunities, and potential areas for growth
  • Build crawlers and competitive intelligence tools to provide MoonPay with deep insights on competitor behavior across the Web3 ecosystem
  • Utilize data-driven insights to forecast, experiment, and demonstrate the incrementality of monetization strategies, making data-informed recommendations on revenue optimization opportunities
  • Build data pipelines and dashboards to give leadership visibility on the performance of pricing experiments
  • Architect incentive and reward mechanisms tailored to boost retention, while obsessing over the finer details that elevate the end-to-end product experience
  • Create monetization strategies for new product lines, leveraging robust margin simulations and detailed financial modeling to inform decision-making
  • Structure B2B and enterprise agreements with rigor around unit economics, balancing growth ambitions with margin integrity
  • Collaborate with cross-functional teams, including Product, Engineering, FP&A, Data, and BD, to implement and execute monetization strategies effectively




What You Will Need

  • Proven experience in growth analytics and monetization (pricing, promotions, rewards, and loyalty programs) functions, with examples of implementing successful monetization strategies within a Consumer product
  • Track record of designing and implementing high-impact incentive and reward systems that drive user engagement and retention
  • Hands-on experience in building adaptive, data-driven pricing algorithms tailored to marketplaces and dynamic conditions
  • Strong analytical and quantitative skills, with proficiency in elasticity modeling and a good grasp of statistics, experimentation, and causal inference
  • Understanding of pricing strategies and revenue optimization in B2C / B2B2C / B2B environments, with more emphasis on B2C and B2B2C
  • Excellent communication and presentation skills to effectively communicate strategies and recommendations to stakeholders
  • Ability to work in extremely fast-paced environments, managing multiple priorities and meeting deadlines
  • Proficiency in SQL (BigQuery), Python, Git/GitHub, and preferably Looker (Tableau or PowerBI are acceptable as well)
  • Above average knowledge of DBT, Docker, GCP, and Airflow
  • Experience in the cryptocurrency industry, fintech sector, or platform-type businesses is preferred but not required




Personal Attributes

  • Analytical mindset with a passion for data-driven decision-making
  • Strong strategic thinking and problem-solving abilities
  • Self-motivated and proactive, with a strong sense of ownership and accountability
  • Problem solver, grounded in user problems, combined with strong first principles thinking to drive efficient solutions
  • Highly ambitious with a results-oriented attitude and continuous improvement mindset




Technologies you will work with

  • Python
  • SQL (BigQuery)
  • GCP
  • EPPO for experimentation
  • DBT, Docker, Cloud Run/Kubernetes, and Airflow for data orchestration and data pipelines
  • Looker data visualization
  • Git and GitHub for code collaboration
  • Ability to leverage AI tools such as Cursor and LLMs in the day-to-day work
  • Nice to have, but can be learned on the job:
  • Experience with web and/or app Scraping
  • TypeScript (just the ability to understand the logic, not necessarily write code)
  • DataDog (just the ability to write queries)
  • LaunchDarkly (just the ability to change feature flag rules manually or programmatically)
  • Postman for testing API calls




We’re looking for people who live our core values, those who strive for excellence and want to leave a lasting legacy on the global financial system. Our values:

B - Be Hungry

L - Level Up

O - Own It

C - Crypto Curious

K - Kaizen

What’s in it for you

Competitive salary package

Equity package: We believe financial freedom starts with our employees, so all employees have ownership at MoonPay

Pay for performance equity bonus: Those who drive outsized outcomes receive outsized rewards

Unlimited holidays: We give you the autonomy to choose when to work (and when to switch off)

Hybrid working schedule: Work fully remotely or your nearest Moonbase, the choice is yours

???? Private Healthcare benefits: To protect you and your loved ones

Enhanced parental leave: So you can spend more time with your loved ones without a second thought

Annual training budget: We support your training journey every step of the way

???? Home office setup allowance: Create the home office of your dreams

Remote working allowance: Those working fully remotely get a little extra for utilities

Monthly budget to spend on our products and zero fee crypto transactions: Cultivate your inner DEGEN

Employee referral programme: Great people know great people, refer them to receive 10K in USDC

️ Regular remote company offsites: Meet your colleagues regularly for high impact in person sessions and hackathons

Working in a disruptive and fast-growing company where excellence is rewarded

What’s it like to work at MoonPay?

At MoonPay, you’ll work alongside driven, resourceful people who are passionate about excellence in everything they do. Kaizen is more than just a saying here, it’s a mindset. We encourage you to think big, take risks, and push the boundaries of what’s possible, knowing you have the support of a team that wants to see you grow. We’re listed in the Sunday Times best places to work guide and consistently strive to provide an environment where everyone feels they can their best work.

Whether you’re remote or collaborating with teammates around the world, you’ll find opportunities here to do the best work of your career while shaping the future of the decentralized economy.

Commitment To Diversity
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 learnt, diversity cannot.

Please let us know if you require any accommodations for the interview process, and we’ll do our best to provide assistance.

At MoonPay we believe that every voice matters. We strive to create a mindful and respectful environment where everyone can bring their authentic self to work, and experience a culture that is free of harassment, racism, and discrimination. That’s why we are committed to diversity and inclusion in the workplace and are a proud equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status or any other characteristic protected by law. This policy applies to all employment practices within our organization, including, but not limited to, hiring, recruiting, promotion, termination, layoff, and leave of absence.MoonPay is also committed to providing reasonable accommodations in our job application procedures for qualified individuals with disabilities. Please inform our Talent Team if you need any assistance completing any forms or to otherwise participate in the application process.

Please be aware that MoonPay does not request an AI-led interview without seeing a recruiter or team member from MoonPay on video call. We won't ask for your personal identification documents or any money from you during your interview process with us. Be fraud smart! If you receive an email - claiming to be from MoonPay - but from an email address ending in anything other than @moonpay.com, please be aware that this is not us.Seniority level

  • Seniority levelNot Applicable

Employment type

  • Employment typeFull-time

Job function

  • Job functionEngineering and Information Technology
  • IndustriesHospitality, Food and Beverage Services, and Retail

Referrals increase your chances of interviewing at MoonPay by 2x

Get notified about new Data Scientist jobs in London, England, United Kingdom.

London, England, United Kingdom 3 days ago

London, England, United Kingdom 1 week ago

Greater London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 month ago

Greater London, England, United Kingdom £35,000.00-£45,000.00 10 hours ago

Greater London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 5 days ago

London, England, United Kingdom 2 days ago

London, England, United Kingdom 4 weeks ago

London, England, United Kingdom 2 weeks ago

Data Scientist – Data Science Analytics and Enablement (DSAE)

London, England, United Kingdom 1 day ago

London, England, United Kingdom 1 month ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 month ago

Data Scientist, Internship, United Kingdom - BCG X

London, England, United Kingdom 1 week ago

London, England, United Kingdom 1 week ago

London, England, United Kingdom 2 hours ago

London, England, United Kingdom 2 months ago

London, England, United Kingdom 2 weeks ago

Greater London, England, United Kingdom 2 weeks ago

London, England, United Kingdom 1 week ago

Surrey, England, United Kingdom 12 hours ago

Data Scientist – Experimentation & Measurement

London, England, United Kingdom 1 day ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 7 months ago

London, England, United Kingdom 2 weeks ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

Related Jobs

View all jobs

Staff Data Scientist

Data Scientist – CLV & Next Best Action United Kingdom, London

MMM Data Scientist

Data Scientist Newcastle (GB) Professionals

Lead Data Scientist - Healthcare

Lead Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.