Job Description
Summary
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
Skills
- Analytical Thinking
- Communications Skills
- Development
- Python
- Software Engineering
- SQL
- Strategic Thinking
- Team Collaboration